* move unets to module 🦋
* parameterize unet-level import.
* fix flax unet2dcondition model import
* models __init__
* mildly depcrecating models.unet_2d_blocks in favor of models.unets.unet_2d_blocks.
* noqa
* correct depcrecation behaviour
* inherit from the actual classes.
* Empty-Commit
* backwards compatibility for unet_2d.py
* backward compatibility for unet_2d_condition
* bc for unet_1d
* bc for unet_1d_blocks
* - extract function for stage in UNet2DConditionModel init & forward
- Add new function get_mid_block() to unet_2d_blocks.py
* add type hint to get_mid_block aligned with get_up_block and get_down_block; rename _set_xxx function
* add type hint and use keyword arguments
* remove `copy from` in versatile diffusion
* [Fix] Multiple image conditionings in a single batch for `StableDiffusionControlNetPipeline`.
* Refactor `check_inputs` in `StableDiffusionControlNetPipeline` to avoid redundant codes.
* Make the behavior of MultiControlNetModel to be the same to the original ControlNetModel
* Keep the code change minimum for nested list support
* Add fast test `test_inference_nested_image_input`
* Remove redundant check for nested image condition in `check_inputs`
Remove `len(image) == len(prompt)` check out of `check_image()`
Co-authored-by: YiYi Xu <yixu310@gmail.com>
* Better `ValueError` message for incompatible nested image list size
Co-authored-by: YiYi Xu <yixu310@gmail.com>
* Fix syntax error in `check_inputs`
* Remove warning message for multi-ControlNets with multiple prompts
* Fix a typo in test_controlnet.py
Co-authored-by: YiYi Xu <yixu310@gmail.com>
* Add test case for multiple prompts, single image conditioning in `StableDiffusionMultiControlNetPipelineFastTests`
* Improved `ValueError` message for nested `controlnet_conditioning_scale`
* Documenting the behavior of image list as `StableDiffusionControlNetPipeline` input
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Co-authored-by: YiYi Xu <yixu310@gmail.com>
* Enable image resizing to adjust its height and width in StableDiffusionXLInstructPix2PixPipeline
* Ensure that validation is performed at every 'validation_step', not at every step
* fix: training resume from fp16.
* add: comment
* remove residue from another branch.
* remove more residues.
* thanks to Younes; no hacks.
* style.
* clean things a bit and modularize _set_state_dict_into_text_encoder
* add comment about the fix detailed.
* Remove conversion to RGB
* Add a Conversion Function
* Add type hint for convert_method
* Update src/diffusers/utils/loading_utils.py
Update docstring
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update docstring
* Optimize imports
* Optimize imports (2)
* Reformat code
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Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sayak Paul <spsayakpaul@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
* I added a new doc string to the class. This is more flexible to understanding other developers what are doing and where it's using.
* Update src/diffusers/models/unet_2d_blocks.py
This changes suggest by maintener.
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* Update src/diffusers/models/unet_2d_blocks.py
Add suggested text
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* Update unet_2d_blocks.py
I changed the Parameter to Args text.
* Update unet_2d_blocks.py
proper indentation set in this file.
* Update unet_2d_blocks.py
a little bit of change in the act_fun argument line.
* I run the black command to reformat style in the code
* Update unet_2d_blocks.py
similar doc-string add to have in the original diffusion repository.
* Batter way to write binarize function
* Solve check_code_quality error
* My mistake to run pull request but not reformated file
* Update image_processor.py
* remove extra variable and space
* Update image_processor.py
* Run ruff libarary to reformat my file
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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>
* Add unload_ip_adapter method
* Update attn_processors with original layers
* Add test
* Use set_default_attn_processor
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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
