GitLab

* [Examples] Correct path

* uP

* add 'conda install cudatoolkit' to dreambooth 'training on 16GB' example 

fixes https://github.com/huggingface/diffusers/issues/1207



* Apply suggestions from code review
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Make errors for invalid options without "--with_prior_preservation"

* Make --instance_prompt required

* Removed needless check because --instance_data_dir is marked with required

* Updated messages

* Use logger.warning instead of raise errors
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

load text encoder from subfolder

fix sample batch size

Update README.md

fixed typo

* [Better scheduler docs] Improve usage examples of schedulers

* finish

* fix warnings and add test

* finish

* more replacements

* adapt fast tests hf token

* correct more

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

* Integrate compatibility with euler
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* [Flax] Add DreamBooth

* fix sample rng

* style

* not reuse rng

* add dtype for mixed precision training

* Add Flax example

Set train mode for text encoder

make input_args optional

* Make training code usable by external scripts

Add parameter inputs to training and argument parsing function to allow this script to be used by an external call.

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

* Add --pretrained_model_name_revision option to train_dreambooth.py

* Renamed --pretrained_model_name_revision to --revision

* Add an underscore to filename if it already exists

* Use sha1sum hash instead of adding underscores

dont' use safety check when generating prior images

Add --sample_batch_size=1 to the 8 GB dreambooth script

* allow fine-tuning text encoder

* fix a few things

* update readme

Fix dreambooth loss type with prior preservation

* Support deepspeed

* Dreambooth DeepSpeed documentation

* Remove unnecessary casts, documentation

Due to recent commits some casts to half precision are not necessary
anymore.

Mention that DeepSpeed's version of Adam is about 2x faster.

* Review comments

* Fix push_to_hub for dreambooth and textual_inversion

* Use repo.push_to_hub instead of push_to_hub

up

remove use_auth_token

using already created `Path` in dataset

* Fix typos

* Update examples/dreambooth/train_dreambooth.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

fix applying clip grad norm

update transfomrers version in example

update install section

don't pass tensor_format

* Add training example for DreamBooth.

* Fix bugs.

* Update readme and default hyperparameters.

* Reformatting code with black.

* Update for multi-gpu trianing.

* Apply suggestions from code review

* improgve sampling

* fix autocast

* improve sampling more

* fix saving

* actuallu fix saving

* fix saving

* improve dataset

* fix collate fun

* fix collate_fn

* fix collate fn

* fix key name

* fix dataset

* fix collate fn

* concat batch in collate fn

* add grad ckpt

* add option for 8bit adam

* do two forward passes for prior preservation

* Revert "do two forward passes for prior preservation"

This reverts commit 661ca4677e6dccc4ad596c2ee6ca4baad4159e95.

* add option for prior_loss_weight

* add option for clip grad norm

* add more comments

* update readme

* update readme

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

* add docstr for dataset

* update the saving logic

* Update examples/dreambooth/README.md

* remove unused imports
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>