GitLab

* 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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* Kolors additional pipelines, community contrib

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Co-authored-by: Teriks <Teriks@users.noreply.github.com>
Co-authored-by: Linoy Tsaban <57615435+linoytsaban@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>
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* fix issue that training flux controlnet was unstable and validation results were unstable

* del unused code pieces, fix grammar

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.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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Fix: `StableDiffusionXLControlNetAdapterInpaintPipeline` incorrectly inherited `StableDiffusionLoraLoaderMixin` (#11357)

Fix: Inherit `StableDiffusionXLLoraLoaderMixin`

`StableDiffusionXLControlNetAdapterInpaintPipeline`
used to incorrectly inherit
`StableDiffusionLoraLoaderMixin`
instead of `StableDiffusionXLLoraLoaderMixin`

* post release

* update

* fix deprecations

* remaining

* update

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

* update

* update

* update

* update

* fix: SD3 ControlNet validation so that it runs on a A100.

* use backend-agnostic cache and pass devide.

* 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

---------
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

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

[train_controlnet.py] Fix the LR schedulers when num_train_epochs is passed in a distributed training env (#8461)

* Create diffusers.yml

* fix num_train_epochs

* Delete diffusers.yml

* Fixed Changes

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

* Add stg wan to community pipelines

* remove debug prints

* remove unused comment

* Update doc

* Add credit + fix typo

* Apply style fixes

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* Fixed requests.get function call by adding timeout parameter.

* declare DIFFUSERS_REQUEST_TIMEOUT in constants and import when needed

* remove unneeded os import

* Apply style fixes

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Co-authored-by: Sai-Suraj-27 <sai.suraj.27.729@gmail.com>
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

* model card gen code

* push modelcard creation

* remove optional from params

* add import

* add use_dora check

* correct lora var use in tags

* make style && make quality

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Co-authored-by: Aryan <aryan@huggingface.co>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* feat: [Community Pipeline] - FaithDiff Stable Diffusion XL Pipeline for Image SR.

* added pipeline

* [Documentation] Update README and example code with additional usage instructions for AnyText

* [Documentation] Update README for AnyTextPipeline and improve logging in code

* Remove wget command for font file from example docstring in anytext.py

Add 4 Notebooks and update the missing links for the
example README.

* add disc_optimizer step (not fix)

* support syncbatchnorm in discriminator

Co-authored-by: Juan Acevedo <jfacevedo@google.com>

* cogview4 control training


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Co-authored-by: OleehyO <leehy0357@gmail.com>
Co-authored-by: yiyixuxu <yixu310@gmail.com>

reverts accidental change that removes attn_mask in attn. Improves flux ptxla by using flash block sizes. Moves encoding outside the for loop.
Co-authored-by: Juan Acevedo <jfacevedo@google.com>

[examples/controlnet/train_controlnet_sd3.py] Fixes #11050 - Cast prompt_embeds and pooled_prompt_embeds to weight_dtype to prevent dtype mismatch (#11051)

Fix: dtype mismatch of prompt embeddings in sd3 controlnet training
Co-authored-by: Andreas Jörg <andreasjoerg@MacBook-Pro-von-Andreas-2.fritz.box>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

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

small fix on generating time_ids & embeddings

* Add initial template

* Second template

* feat: Add TextEmbeddingModule to AnyTextPipeline

* feat: Add AuxiliaryLatentModule template to AnyTextPipeline

* Add bert tokenizer from the anytext repo for now

* feat: Update AnyTextPipeline's modify_prompt method

This commit adds improvements to the modify_prompt method in the AnyTextPipeline class. The method now handles special characters and replaces selected string prompts with a placeholder. Additionally, it includes a check for Chinese text and translation using the trans_pipe.

* Fill in the `forward` pass of `AuxiliaryLatentModule`

* `make style && make quality`

* `chore: Update bert_tokenizer.py with a TODO comment suggesting the use of the transformers library`

* Update error handling to raise and logging

* Add `create_glyph_lines` function into `TextEmbeddingModule`

* make style

* Up

* Up

* Up

* Up

* Remove several comments

* refactor: Remove ControlNetConditioningEmbedding and update code accordingly

* Up

* Up

* up

* refactor: Update AnyTextPipeline to include new optional parameters

* up

* feat: Add OCR model and its components

* chore: Update `TextEmbeddingModule` to include OCR model components and dependencies

* chore: Update `AuxiliaryLatentModule` to include VAE model and its dependencies for masked image in the editing task

* `make style`

* refactor: Update `AnyTextPipeline`'s docstring

* Update `AuxiliaryLatentModule` to include info dictionary so that text processing is done once

* simplify

* `make style`

* Converting `TextEmbeddingModule` to ordinary `encode_prompt()` function

* Simplify for now

* `make style`

* Up

* feat: Add scripts to convert AnyText controlnet to diffusers

* `make style`

* Fix: Move glyph rendering to `TextEmbeddingModule` from `AuxiliaryLatentModule`

* make style

* Up

* Simplify

* Up

* feat: Add safetensors module for loading model file

* Fix device issues

* Up

* Up

* refactor: Simplify

* refactor: Simplify code for loading models and handling data types

* `make style`

* refactor: Update to() method in FrozenCLIPEmbedderT3 and TextEmbeddingModule

* refactor: Update dtype in embedding_manager.py to match proj.weight

* Up

* Add attribution and adaptation information to pipeline_anytext.py

* Update usage example

* Will refactor `controlnet_cond_embedding` initialization

* Add `AnyTextControlNetConditioningEmbedding` template

* Refactor organization

* style

* style

* Move custom blocks from `AuxiliaryLatentModule` to `AnyTextControlNetConditioningEmbedding`

* Follow one-file policy

* style

* [Docs] Update README and pipeline_anytext.py to use AnyTextControlNetModel

* [Docs] Update import statement for AnyTextControlNetModel in pipeline_anytext.py

* [Fix] Update import path for ControlNetModel, ControlNetOutput in anytext_controlnet.py

* Refactor AnyTextControlNet to use configurable conditioning embedding channels

* Complete control net conditioning embedding in AnyTextControlNetModel

* up

* [FIX] Ensure embeddings use correct device in AnyTextControlNetModel

* up

* up

* style

* [UPDATE] Revise README and example code for AnyTextPipeline integration with DiffusionPipeline

* [UPDATE] Update example code in anytext.py to use correct font file and improve clarity

* down

* [UPDATE] Refactor BasicTokenizer usage to a new Checker class for text processing

* update pillow

* [UPDATE] Remove commented-out code and unnecessary docstring in anytext.py and anytext_controlnet.py for improved clarity

* [REMOVE] Delete frozen_clip_embedder_t3.py as it is in the anytext.py file

* [UPDATE] Replace edict with dict for configuration in anytext.py and RecModel.py for consistency

* 🆙



* style

* [UPDATE] Revise README.md for clarity, remove unused imports in anytext.py, and add author credits in anytext_controlnet.py

* style

* Update examples/research_projects/anytext/README.md
Co-authored-by: Aryan <contact.aryanvs@gmail.com>

* Remove commented-out image preparation code in AnyTextPipeline

* Remove unnecessary blank line in README.md

* Support STG for video pipelines

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Update pipeline_stg_cogvideox.py

* Update pipeline_stg_hunyuan_video.py

* Update pipeline_stg_ltx.py

* Update pipeline_stg_ltx_image2video.py

* Update pipeline_stg_mochi.py

* Update pipeline_stg_hunyuan_video.py

* Update pipeline_stg_ltx.py

* Update pipeline_stg_ltx_image2video.py

* Update pipeline_stg_mochi.py

* update

* remove rescaling

* Apply style fixes

---------
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* add cogvideox ddim inversion script

* implement as a pipeline, and add documentation

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

Bumps [jinja2](https://github.com/pallets/jinja) from 3.1.5 to 3.1.6.
- [Release notes](https://github.com/pallets/jinja/releases)
- [Changelog](https://github.com/pallets/jinja/blob/main/CHANGES.rst)
- [Commits](https://github.com/pallets/jinja/compare/3.1.5...3.1.6

)

---
updated-dependencies:
- dependency-name: jinja2
  dependency-type: direct:production
...
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

[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 t5 training bug

* Apply style fixes

---------
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* feat: add Mixture-of-Diffusers ControlNet Tile upscaler Pipeline for SDXL

* make style make quality

* 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>