GitLab

* Fix SD scripts - there are only 2 items per batch

* Adjustments to make the SDXL scripts work with other datasets

* Use public webdataset dataset for examples

* make style

* Minor tweaks to the readmes.

* Stress that the database is illustrative.

* debug

* from step

* print

* turn sigma a list

* make str

* init_noise_sigma

* comment

* remove prints

* feat: introduce fused projections

* change to a better name

* no grad

* device.

* device

* dtype

* okay

* print

* more print

* fix: unbind -> split

* fix: qkv >-> k

* enable disable

* apply attention processor within the method

* attn processors

* _enable_fused_qkv_projections

* remove print

* add fused projection to vae

* add todos.

* add: documentation and cleanups.

* add: test for qkv projection fusion.

* relax assertions.

* relax further

* fix: docs

* fix-copies

* correct error message.

* Empty-Commit

* better conditioning on disable_fused_qkv_projections

* check

* check processor

* bfloat16 computation.

* check latent dtype

* style

* remove copy temporarily

* cast latent to bfloat16

* fix: vae -> self.vae

* remove print.

* add _change_to_group_norm_32

* comment out stuff that didn't work

* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* reflect patrick's suggestions.

* fix imports

* fix: disable call.

* fix more

* fix device and dtype

* fix conditions.

* fix more

* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

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Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* utils and test modifications to enable device agnostic testing

* device for manual seed in unet1d

* fix generator condition in vae test

* consistency changes to testing

* make style

* add device agnostic testing changes to source and one model test

* make dtype check fns private, log cuda fp16 case

* remove dtype checks from import utils, move to testing_utils

* adding tests for most model classes and one pipeline

* fix vae import

* Update train_dreambooth_lora_sdxl_advanced.py

* remove global function args from dreamboothdataset class

* style

* style

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

* Update pipeline_demofusion_sdxl.py

* Update README.md

* fix

* fix ldm conversion

* fix linting

pinn ruff

move kandinsky convert script

* copied from section

* feedback

* add

* fix api docs

* edits

* improve help tags

* style fix

* changes token_abstraction type to string.
support multiple concepts for pivotal using a comma separated string.

* style fixup

* changed logger to warning (not yet available)

* moved the token_abstraction parsing to be in the same block as where we create the mapping of identifier to token

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Co-authored-by: Linoy <linoy@huggingface.co>

* Add files via upload

* Update README.md

* Update pipeline_demofusion_sdxl.py

* Update pipeline_demofusion_sdxl.py

* Update examples/community/README.md
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

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

* Support IP-Adapter Plus

* fix format

* restore before black format

* restore before black format

* generic

* Refactor PerceiverAttention

* format

* fix test and refactor PerceiverAttention

* generic encode_image

* keep attention implementation

* merge tests

* encode_image backward compatible

* code quality

* fix controlnet inpaint pipeline

* refactor FFN

* refactor FFN

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

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

* update setup and deps table

* update

* update

* update

* up

* up

* update

* up

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* quality fix

* fix failure reporting

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Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update value_guided_sampling.py

Changed the scheduler step function as predict_epsilon parameter is not there in latest  DDPM Scheduler

* Update value_guided_sampling.md

Updated a link to a working notebook

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

* improve help tags

* style fix

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Co-authored-by: Linoy <linoy@huggingface.co>

* fix: duplicate unet prefix problem.

* Update src/diffusers/loaders/lora.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

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Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

remove fast tests from slow suite

* adapt PixArtAlphaPipeline for pixart-lcm model

* remove original_inference_steps from __call__

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

* LLMGroundedDiffusionPipeline: inherit from DiffusionPipeline and fix peft

* Use main in the revision in the examples

* Add "Copied from" statements in comments

* Fix formatting with ruff

* Post Release: v0.24.0

* post pone deprecation

* post pone deprecation

* Add model_index.json

* fix dpm
* all scheulers

clean-up kendinsky 3.0

* Update the location of Python's version

* Trim trailing whitespace

Fix assertion bug

* Update README.md

* Update README.md

* Add files via upload

* Update README.md

* Update examples/community/README.md

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Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

Allow text encoder to be passed

minor edits to setup

Update svd.md

readme

[examples/advanced_diffusion_training] bug fixes and improvements for LoRA Dreambooth SDXL advanced training script (#5935)

* imports and readme bug fixes

* bug fix - ensures text_encoder params are dtype==float32 (when using pivotal tuning) even if the rest of the model is loaded in fp16

* added pivotal tuning to readme

* mapping token identifier to new inserted token in validation prompt (if used)

* correct default value of --train_text_encoder_frac

* change default value of  --adam_weight_decay_text_encoder

* validation prompt generations when using pivotal tuning bug fix

* style fix

* textual inversion embeddings name change

* style fix

* bug fix - stopping text encoder optimization halfway

* readme - will include token abstraction and new inserted tokens when using pivotal tuning
- added type to --num_new_tokens_per_abstraction

* style fix

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Co-authored-by: Linoy Tsaban <linoy@huggingface.co>

Update __init__.py

* make `requires_safety_checker` a kwarg instead of a positional argument as it's more future-proof

* apply `make style` formatting edits

* add image_encoder to arguments and pass to super constructor

Update svd.md