GitLab

* Modularized the train_lora_sdxl file

* Modularized the train_lora_sdxl file

* Modularized the train_lora_sdxl file

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

* Modularized the train_lora file

* Modularized the train_lora file

* Modularized the train_lora file

* Modularized the train_lora file

* Modularized the train_lora file

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

* post release v0.28.0

* style

Update requirements.txt

If the datasets library is old, it will not read the metadata.jsonl and the label will default to an integer of type int.
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

Co-authored-by: mhh001 <mahonghao1@huawei.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

fix bugs when using deepspeed
Co-authored-by: mhh001 <mahonghao1@huawei.com>

* 7879 - adjust documentation to use naruto dataset, since pokemon is now gated

* replace references to pokemon in docs

* more references to pokemon replaced

* Japanese translation update

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Co-authored-by: bghira <bghira@users.github.com>

Add Ascend NPU support for SDXL fine-tuning and fix the model saving bug when using DeepSpeed. (#7816)

* Add Ascend NPU support for SDXL fine-tuning and fix the model saving bug when using DeepSpeed.

* fix check code quality

* Decouple the NPU flash attention and make it an independent module.

* add doc and unit tests for npu flash attention.

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Co-authored-by: mhh001 <mahonghao1@huawei.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

A new function compute_dream_and_update_latents has been added to the
training utilities that allows you to do DREAM rectified training in line
with the paper https://arxiv.org/abs/2312.00210. The method can be used
with an extra argument in the train_text_to_image.py script.

Co-authored-by: Jimmy <39@🇺🇸.com>

* Restore unet params back to normal from EMA when validation call is finished

* empty commit

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

* 7529 do not disable autocast for cuda devices

* Remove typecasting error check for non-mps platforms, as a correct autocast implementation makes it a non-issue

* add autocast fix to other training examples

* disable native_amp for dreambooth (sdxl)

* disable native_amp for pix2pix (sdxl)

* remove tests from remaining files

* disable native_amp on huggingface accelerator for every training example that uses it

* convert more usages of autocast to nullcontext, make style fixes

* make style fixes

* style.

* Empty-Commit

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

* apple mps: training support for SDXL LoRA

* sdxl: support training lora, dreambooth, t2i, pix2pix, and controlnet on apple mps

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

delete vae and text encoders after use
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* post-release

* quality

* log loss per image

* add commandline param for per image loss logging

* style

* debug-loss -> debug_loss

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

switch to logger.warning

* add tags for diffusers training

* add tags for diffusers training

* add tags for diffusers training

* add tags for diffusers training

* add tags for diffusers training

* add tags for diffusers training

* add dora tags for drambooth lora scripts

* style

* Speed up dataset mapping

* Fix missing columns

* Remove cache files cleanup

* Update examples/text_to_image/train_text_to_image_sdxl.py

* make style

* Fix code style

* style

* Empty-Commit

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Quentin Lhoest <42851186+lhoestq@users.noreply.github.com>
Co-authored-by: Quentin Lhoest <lhoest.q@gmail.com>

Update train_text_to_image_sdxl.py

* Fix typos

* Refactor save_model_card function to handle images and repo_folder parameters

* Discard changes to examples/text_to_image/train_text_to_image.py

* Discard changes to examples/text_to_image/train_text_to_image_lora_sdxl.py

* Update train_text_to_image_lora.py

* Update train_text_to_image_sdxl.py

Update copyright information and fix typos in text_to_image examples

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

* standardize model card template t2i-lora-sdxl

* type annotations

standardize model card template t2i-sdxl

standardize model card t2i-lora

* standardize model card

* fix base_model

* post release

* style

* Empty-Commit

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

change to 2024

* Fix mixed precision fine-tuning for text-to-image-lora-sdxl example.

* fix text_encoder_two bug.

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Co-authored-by: Sajad Norouzi <sajadn@dev-dsk-sajadn-2a-87239470.us-west-2.amazon.com>

* fix minsnr implementation for v-prediction case

* format code

* always compute snr when snr_gamma is specified

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

* Fixed the bug related to saving DeepSpeed models.

* Add information about training SD models using DeepSpeed to the README.

* Apply suggestions from code review

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Co-authored-by: mhh001 <mahonghao1@huawei.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Update train_text_to_image_sdxl.py

* Update train_text_to_image_lora_sdxl.py

make compile compatible

make compile compatible

* torch compatible

* code quality fix

* ruff style

* ruff format

create a utility for casting the lora params during training.

* added unwrapper

* fiz typo