GitLab

increase the time of timeout when using big dataset or high resolution

* add dreambooth lora script for SDXL incorporating latest changes.

* remove use_auth_token=True.

* add: documentation

* remove unneeded cli.

* increase the number of training steps in the readme.

* add LoraLoaderMixin to the subclassing mix.

* add sdxl lora dreambooth test.

* add: inference code sample.

* add: refiner output.

* add LoraLoaderMixin to the mix of classes of StableDiffusionXLImg2ImgPipeline.

* change default resolution of DreamBoothDataset.

* better sdxl report path.

* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

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Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* refactor to support patching LoRA into T5

instantiate the lora linear layer on the same device as the regular linear layer

get lora rank from state dict

tests

fmt

can create lora layer in float32 even when rest of model is float16

fix loading model hook

remove load_lora_weights_ and T5 dispatching

remove Unet#attn_processors_state_dict

docstrings

* text encoder monkeypatch class method

* fix test

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

* improve sd xl

* correct more

* finish

* make style

* fix more

* avoid upcasting by assigning dtype to noise tensor

* make style

* Update train_unconditional.py

* Update train_unconditional.py

* make style

* add unit test for pickle

* revert change

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Co-authored-by: root <root@orttrainingdev8.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Prathik Rao <prathikrao@microsoft.com@orttrainingdev8.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>

* - Added validation parameters
- Changed some parameter descriptions to better explain their use.
- Fixed a few typos.
- Added concept_list parameter for better management of multiple subjects
- changed logic for image validation

* - Fixed bad logic for class data root directories

* Defaulting validation_steps to None for an easier logic

* Fixed multiple validation prompts

* Fixed bug on validation negative prompt

* Changed validation logic for tracker.

* Added uuid for validation image labeling

* Fix error when comparing validation prompts and validation negative prompts

* Improved error message when negative prompts for validation are more than the number of prompts

* - Changed image tracking number from epoch to global_step
- Added Typing for functions

* Added some validations more when using concept_list parameter and the regular ones.

* Fixed error message

* Added more validations for validation parameters

* Improved messaging for errors

* Fixed validation error for parameters with default values

* - Added train step to image name for validation
- reformatted code

* - Added train step to image's name for validation
- reformatted code

* Updated README.md file.

* reverted back original script of train_dreambooth.py

* reverted back original script of train_dreambooth.py

* left one blank line at the eof

* reverted back setup.py

* reverted back setup.py

* added same logic for when parameters for prior preservation are used without enabling the flag while using concept_list parameter.

* Ran black formatter.

* fixed a few strings

* fixed import sort with isort and removed fstrings without placeholder

* fixed import order with ruff (since with isort wasn't ok)

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

* add rank args in lora finetune

* del network_alpha

* refactor: readme serialized from the example when push_to_hub is True.

* fix: batch size arg.

* a bit better formatting

* minor fixes.

* add note on env.

* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* condition wandb info better

* make mixed_precision assignment in cli args explicit.

* separate inference block for sample images.

* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* address more comments.

* autocast mode.

* correct none image type problem.

* ifx: list assignment.

* minor fix.

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Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

add note to loading from checkpoint

* manual check for checkpoints_total_limit instead of using accelerate

* remove controlnet_conditioning_embedding_out_channels

* Maintain same decoder start noise for all interp steps

* Correct comment

* use batch_size for consistency

* relax tolerance slightly

* correct incorrect naming

* update reference pipeline

* update reference pipeline

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

* Post release

* Post release

Apply deprecations

* added StableDiffusionCanvasPipeline pipeline

* Added utils codes to pipe_utils file.

* make style

* delete mixture.py and Text2ImageRegion class

* make style

* Added the codes to the readme.md file.

* Moved functions from pipeline_utils to mix_canvas

* Implement option for rescaling betas to zero terminal SNR

* Implement rescale classifier free guidance in pipeline_stable_diffusion.py

* focus on DDIM

* make style

* make style

* make style

* make style

* Apply suggestions from Peter Lin

* Apply suggestions from Peter Lin

* make style

* Apply suggestions from code review

* Apply suggestions from code review

* make style

* make style

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Co-authored-by: MaxWe00 <gitlab.9v1lq@slmail.me>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* feat: add lora attention processor for pt 2.0.

* explicit context manager for SDPA.

* switch to flash attention

* make shapes compatible to work optimally with SDPA.

* fix: circular import problem.

* explicitly specify the flash attention kernel in sdpa

* fall back to efficient attention context manager.

* remove explicit dispatch.

* fix: removed processor.

* fix: remove optional from type annotation.

* feat: make changes regarding LoRAAttnProcessor2_0.

* remove confusing warning.

* formatting.

* relax tolerance for PT 2.0

* fix: loading message.

* remove unnecessary logging.

* add: entry to the docs.

* add: network_alpha argument.

* relax tolerance.

Correct multi gpu

Expose num_cycles kwarg of get_schedule() through args.lr_num_cycles.

* dreambooth if docs - stage II, more info

* Update docs/source/en/training/dreambooth.mdx
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update docs/source/en/training/dreambooth.mdx
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update docs/source/en/training/dreambooth.mdx
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* download instructions for downsized images

* update source README to match docs

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

* add tensorrt inpaint pipeline
Signed-off-by: Asfiya Baig <asfiyab@nvidia.com>

* run make style
Signed-off-by: Asfiya Baig <asfiyab@nvidia.com>

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Signed-off-by: Asfiya Baig <asfiyab@nvidia.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Updated the filename and readme file.

* reformatter

* reformetter

fixed typo

* add _convert_kohya_lora_to_diffusers

* make style

* add scaffold

* match result: unet attention only

* fix monkey-patch for text_encoder

* with CLIPAttention

While the terrible images are no longer produced,
the results do not match those from the hook ver.
This may be due to not setting the network_alpha value.

* add to support network_alpha

* generate diff image

* fix monkey-patch for text_encoder

* add test_text_encoder_lora_monkey_patch()

* verify that it's okay to release the attn_procs

* fix closure version

* add comment

* Revert "fix monkey-patch for text_encoder"

This reverts commit bb9c61e6faecc1935c9c4319c77065837655d616.

* Fix to reuse utility functions

* make LoRAAttnProcessor targets to self_attn

* fix LoRAAttnProcessor target

* make style

* fix split key

* Update src/diffusers/loaders.py

* remove TEXT_ENCODER_TARGET_MODULES loop

* add print memory usage

* remove test_kohya_loras_scaffold.py

* add: doc on LoRA civitai

* remove print statement and refactor in the doc.

* fix state_dict test for kohya-ss style lora

* Apply suggestions from code review
Co-authored-by: Takuma Mori <takuma104@gmail.com>

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

include the instruction-tuning blog link.

* update dreambooth lora to work with IF stage II

* Update dreambooth script for IF stage II upscaler

* update code to reflect latest changes as of May 30th

* update text to image example

* reflect changes to textual inversion

* make style

* fix typo

* Revert unnecessary readme changes

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Co-authored-by: root <root@orttrainingdev8.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>
Co-authored-by: Prathik Rao <prathikrao@microsoft.com@orttrainingdev8.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>

Make sure we also change the config when setting `encoder_hid_dim_type=="text_proj"` and allow xformers (#3615)

* fix if

* make style

* make style

* add tests for xformers

* make style

* update

* added clip_guided_images_mixing_stable_diffusion file and readme description

* apply pre-commit

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