GitLab

* post-release

* quality

switch to logger.warning

* post release

* style

* Empty-Commit

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

change to 2024

* Fix bug where unet's time_cond_proj_dim is not set correctly if using args.unet_time_cond_proj_dim.

* make style

* post release

* style

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

* Make WDS pipeline interpolation type configurable.

* Make the VAE encoding batch size configurable.

* Make lora_alpha and lora_dropout configurable for LCM LoRA scripts.

* Generalize scalings_for_boundary_conditions function and make the timestep scaling configurable.

* Make LoRA target modules configurable for LCM-LoRA scripts.

* Move resolve_interpolation_mode to src/diffusers/training_utils.py and make interpolation type configurable in non-WDS script.

* apply suggestions from review

* fix

* style fix

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

Fix bug when creating the guidance embeddings using multiple GPUs.
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Clean up comments in LCM(-LoRA) distillation scripts.

* Calculate predicted source noise noise_pred correctly for all prediction_types.

* make style

* apply suggestions from review

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

* Harmonize HF environment variables + deprecate use_auth_token

* fix import

* fix

* Fix SD scripts - there are only 2 items per batch

* Adjustments to make the SDXL scripts work with other datasets

* Use public webdataset dataset for examples

* make style

* Minor tweaks to the readmes.

* Stress that the database is illustrative.

* Post Release: v0.24.0

* post pone deprecation

* post pone deprecation

* Add model_index.json

* Fix bug related to parsing unet_time_cond_proj_dim.

* Fix analogous bug in the SD-XL LCM distillation script.

* add lcm scripts

* Co-authored-by: dgu8957@gmail.com

* push to hub docs

* fix typo

* feedback

* make style

add controlent script,

* add: utility for image grid.

* add: return type.

* change necessary places.

* add to utility page.

* correct

* correct blocks

* finish

* finish

* finish

* Apply suggestions from code review

* fix

* up

* up

* up

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

* Apply suggestions from code review

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

* honor the original license.

* train_instruct_pix2pix_xl -> train_instruct_pix2pix_sdxl

* 0.20.0dev0

* make style

* up

* Apply suggestions from code review

* Apply suggestions from code review

* up

* fix: #4206

* add: sdxl controlnet training smoketest.

* remove unnecessary token inits.

* add: licensing to model card.

* include SDXL licensing in the model card and make public visibility default

* debugging

* debugging

* disable local file download.

* fix: training test.

* fix: ckpt prefix.

* hash computation. thanks to @lhoestq

* disable dtype casting.

* remove comments.

Remove safety from controlnet

* add: controlnet sdxl.

* modifications to controlnet.

* run styling.

* add: __init__.pys

* incorporate https://github.com/huggingface/diffusers/pull/4019

 changes.

* run make fix-copies.

* resize the conditioning images.

* remove autocast.

* run styling.

* disable autocast.

* debugging

* device placement.

* back to autocast.

* remove comment.

* save some memory by reusing the vae and unet in the pipeline.

* apply styling.

* Allow low precision sd xl

* finish

* finish

* changes to accommodate the improved VAE.

* modifications to how we handle vae encoding in the training.

* make style

* make existing controlnet fast tests pass.

* change vae checkpoint cli arg.

* fix: vae pretrained paths.

* fix: steps in get_scheduler().

* debugging.

* debugging./

* fix: weight conversion.

* add: docs.

* add: limited tests./

* add: datasets to the requirements.

* update docstrings and incorporate the usage of watermarking.

* incorporate fix from #4083

* fix watermarking dependency handling.

* run make-fix-copies.

* Empty-Commit

* Update requirements_sdxl.txt

* remove vae upcasting part.

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

* run make style

* run make fix-copies.

* disable suppot for multicontrolnet.

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

* run make fix-copies.

* dtyle/.

* fix-copies.

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

* Multiply lr scheduler steps by `num_processes`.

* Stop multiplying steps by gradient accumulation.

* manual check for checkpoints_total_limit instead of using accelerate

* remove controlnet_conditioning_embedding_out_channels

* Post release

* Post release

Apply deprecations

do not scale the initial global step by gradient accumulation steps when loading from checkpoint (#3506)

Remove required from tracker_project_name.

As observed by https://github.com/off99555 in https://github.com/huggingface/diffusers/issues/2695#issuecomment-1470755050, it already has a default value.

Write model card in controlnet training script.

* Post release

* fix more

controlnet training center crop input images to multiple of 8

The pipeline code resizes inputs to multiples of 8.
Not doing this resizing in the training script is causing
the encoded image to have different height/width dimensions
than the encoded conditioning image (which uses a separate
encoder that's part of the controlnet model).

We resize and center crop the inputs to make sure they're the
same size (as well as all other images in the batch). We also
check that the initial resolution is a multiple of 8.