GitLab

* feat: enable quantization for hidream lora training.

* better handle compute dtype.

* finalize.

* fix dtype.

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Co-authored-by: Linoy Tsaban <57615435+linoytsaban@users.noreply.github.com>

[train_dreambooth_lora_lumina2] Add LANCZOS as the default interpolation mode for image resizing (#11491)

[ADD] interpolation

[train_dreambooth_lora_sdxl] Add --image_interpolation_mode option for image resizing (default to lanczos) (#11490)

feat(train_dreambooth_lora_sdxl): support --image_interpolation_mode with default to lanczos

* Fix typos in docs and comments

* Apply style fixes

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

remove unnecessary pipeline moving to cpu in validation
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Set LANCZOS as default interpolation mode for resizing

* [train_dreambooth_lora.py] Set LANCZOS as default interpolation mode for resizing

* 1. add pre-computation of prompt embeddings when custom prompts are used as well
2. save model card even if model is not pushed to hub
3. remove scheduler initialization from code example - not necessary anymore (it's now if the base model's config)
4. add skip_final_inference - to allow to run with validation, but skip the final loading of the pipeline with the lora weights to reduce memory reqs

* pre encode validation prompt as well

* Update examples/dreambooth/train_dreambooth_lora_hidream.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Update examples/dreambooth/train_dreambooth_lora_hidream.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Update examples/dreambooth/train_dreambooth_lora_hidream.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* pre encode validation prompt as well

* Apply style fixes

* empty commit

* change default trained modules

* empty commit

* address comments + change encoding of validation prompt (before it was only pre-encoded if custom prompts are provided, but should be pre-encoded either way)

* Apply style fixes

* empty commit

* fix validation_embeddings definition

* fix final inference condition

* fix pipeline deletion in last inference

* Apply style fixes

* empty commit

* layers

* remove readme remarks on only pre-computing when instance prompt is provided and change example to 3d icons

* smol fix

* empty commit

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

Small change
requirements_sana.txt to 
requirements_hidream.txt

* initial commit

* initial commit

* initial commit

* initial commit

* initial commit

* initial commit

* Update examples/dreambooth/train_dreambooth_lora_hidream.py
Co-authored-by: Bagheera <59658056+bghira@users.noreply.github.com>

* move prompt embeds, pooled embeds outside

* Update examples/dreambooth/train_dreambooth_lora_hidream.py
Co-authored-by: hlky <hlky@hlky.ac>

* Update examples/dreambooth/train_dreambooth_lora_hidream.py
Co-authored-by: hlky <hlky@hlky.ac>

* fix import

* fix import and tokenizer 4, text encoder 4 loading

* te

* prompt embeds

* fix naming

* shapes

* initial commit to add HiDreamImageLoraLoaderMixin

* fix init

* add tests

* loader

* fix model input

* add code example to readme

* fix default max length of text encoders

* prints

* nullify training cond in unpatchify for temp fix to incompatible shaping of transformer output during training

* smol fix

* unpatchify

* unpatchify

* fix validation

* flip pred and loss

* fix shift!!!

* revert unpatchify changes (for now)

* smol fix

* Apply style fixes

* workaround moe training

* workaround moe training

* remove prints

* to reduce some memory, keep vae in `weight_dtype` same as we have for flux (as it's the same vae)
https://github.com/huggingface/diffusers/blob/bbd0c161b55ba2234304f1e6325832dd69c60565/examples/dreambooth/train_dreambooth_lora_flux.py#L1207



* refactor to align with HiDream refactor

* refactor to align with HiDream refactor

* refactor to align with HiDream refactor

* add support for cpu offloading of text encoders

* Apply style fixes

* adjust lr and rank for train example

* fix copies

* Apply style fixes

* update README

* update README

* update README

* fix license

* keep prompt2,3,4 as None in validation

* remove reverse ode comment

* Update examples/dreambooth/train_dreambooth_lora_hidream.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Update examples/dreambooth/train_dreambooth_lora_hidream.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* vae offload change

* fix text encoder offloading

* Apply style fixes

* cleaner to_kwargs

* fix module name in copied from

* add requirements

* fix offloading

* fix offloading

* fix offloading

* update transformers version in reqs

* try AutoTokenizer

* try AutoTokenizer

* Apply style fixes

* empty commit

* Delete tests/lora/test_lora_layers_hidream.py

* change tokenizer_4 to load with AutoTokenizer as well

* make text_encoder_four and tokenizer_four configurable

* save model card

* save model card

* revert T5

* fix test

* remove non diffusers lumina2 conversion

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Co-authored-by: Bagheera <59658056+bghira@users.noreply.github.com>
Co-authored-by: hlky <hlky@hlky.ac>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

[train_dreambooth_lora_sdxl.py] Fix the LR Schedulers when num_train_epochs is passed in a distributed training env (#11240)
Co-authored-by: Linoy Tsaban <57615435+linoytsaban@users.noreply.github.com>

* add fix

* add fix

* Apply style fixes

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Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

* post release

* update

* fix deprecations

* remaining

* update

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

* update

* update

* update

* update

* remove custom scheduler

* update requirements.txt

* log_validation with mixed precision

* add intermediate embeddings saving when checkpointing is enabled

* remove comment

* fix validation

* add unwrap_model for accelerator, torch.no_grad context for validation, fix accelerator.accumulate call in advanced script

* revert unwrap_model change temp

* add .module to address distributed training bug + replace accelerator.unwrap_model with unwrap model

* changes to align advanced script with canonical script

* make changes for distributed training + unify unwrap_model calls in advanced script

* add module.dtype fix to dreambooth script

* unify unwrap_model calls in dreambooth script

* fix condition in validation run

* mixed precision

* Update examples/advanced_diffusion_training/train_dreambooth_lora_flux_advanced.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* smol style change

* change autocast

* Apply style fixes

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

* initial

* Update examples/dreambooth/train_dreambooth_lora_sdxl.py
Co-authored-by: hlky <hlky@hlky.ac>

* update

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

[train_dreambooth_lora.py] Fix the LR Schedulers when `num_train_epochs` is passed in a distributed training env (#10973)

* updated train_dreambooth_lora to fix the LR schedulers for `num_train_epochs` in distributed training env

* fixed formatting

* remove trailing newlines

* fixed style error

* Fix seed initialization to handle args.seed = 0 correctly

* Apply style fixes

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

Fix fp16 bug
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* feat: lora support for Lumina2.

* fix-copies.

* updates

* updates

* docs.

* fix

* add: training script.

* tests

* updates

* updates

* major updates.

* updates

* fixes

* docs.

* updates

* updates

* NPU Adaption for Sanna

* NPU Adaption for Sanna

* NPU Adaption for Sanna

* NPU Adaption for Sanna

* NPU Adaption for Sanna

* NPU Adaption for Sanna

* NPU Adaption for Sanna

* NPU Adaption for Sanna

* NPU Adaption for Sanna

* NPU Adaption for Sanna

* NPU Adaption for Sanna

* NPU Adaption for Sanna

* NPU Adaption for Sanna

* NPU Adaption for Sanna

* NPU Adaption for Sanna

* NPU Adaption for Sanna

* NPU Adaption for Sanna

* NPU Adaption for Sanna

* [bugfix]NPU Adaption for Sanna

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Co-authored-by: J石页 <jiangshuo9@h-partners.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* [training] Convert to ImageFolder script

* make

* NPU Adaption for Sanna


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Co-authored-by: J石页 <jiangshuo9@h-partners.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

Remove the FP32 Wrapper
Co-authored-by: Linoy Tsaban <57615435+linoytsaban@users.noreply.github.com>

* enable dreambooth_lora on other devices
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* enable xpu
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* check cuda device before empty cache
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* fix comment
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* import free_memory
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

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Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

change licensing to 2025 from 2024.

Co-authored-by: J石页 <jiangshuo9@h-partners.com>

* add ds support to lora sd3.
Co-authored-by: leisuzz <jiangshuonb@gmail.com>

* style.

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Co-authored-by: leisuzz <jiangshuonb@gmail.com>
Co-authored-by: Linoy Tsaban <57615435+linoytsaban@users.noreply.github.com>

* post release 0.32.0

* stylew

* sana lora training tests and misc.

* remove push to hub

* Update examples/dreambooth/train_dreambooth_lora_sana.py
Co-authored-by: Aryan <aryan@huggingface.co>

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Co-authored-by: Aryan <aryan@huggingface.co>

Update README_sana.md to update the default model

fix: reamde -> readme

* feat: lora support for SANA.

* make fix-copies

* rename test class.

* attention_kwargs -> cross_attention_kwargs.

* Revert "attention_kwargs -> cross_attention_kwargs."

This reverts commit 23433bf9bccc12e0f2f55df26bae58a894e8b43b.

* exhaust 119 max line limit

* sana lora fine-tuning script.

* readme

* add a note about the supported models.

* Apply suggestions from code review
Co-authored-by: Aryan <aryan@huggingface.co>

* style

* docs for attention_kwargs.

* remove lora_scale from pag pipeline.

* copy fix

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Co-authored-by: Aryan <aryan@huggingface.co>

* fix min-snr implementation

https://github.com/kohya-ss/sd-scripts/blob/main/library/custom_train_functions.py#L66



* Update train_dreambooth.py

fix variable name mse_loss_weights

* fix divisor

* make style

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

Add files via upload

* smol change to fix checkpoint saving & resuming (as done in train_dreambooth_sd3.py)

* style

* modify comment to explain reasoning behind hidden size check

* memory improvement as done here: https://github.com/huggingface/diffusers/pull/9829



* fix bug

* fix bug

* style

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

* fix use_dora

* fix style and quality

* fix use_dora with peft version

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

* updated encode prompt and clip encod prompt


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