* fix for lr scheduler in distributed training
* Fixed the recalculation of the total training step section
* Fixed lint error
---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* Add support for _foreach operations and non-blocking to EMAModel
* default foreach to false
* add non-blocking EMA offloading to SD1.5 T2I example script
* fix whitespace
* move foreach to cli argument
* linting
* Update README.md re: EMA weight training
* correct args.foreach_ema
* add tests for foreach ema
* code quality
* add foreach to from_pretrained
* default foreach false
* fix linting
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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: drhead <a@a.a>
* 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>
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>
* 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>
* 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
* 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>
Min-SNR Gamma: correct the fix for SNR weighted loss in v-prediction by adding 1 to SNR rather than the resulting loss weights
Co-authored-by: bghira <bghira@users.github.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* 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>
* 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>
Sayak Paul