* improvement: add typehints and docs to src/diffusers/models/attention_processor.py
* improvement: add typehints and docs to src/diffusers/models/vae.py
* improvement: add missing docs in src/diffusers/models/vq_model.py
* improvement: add typehints and docs to src/diffusers/models/transformer_temporal.py
* improvement: add typehints and docs to src/diffusers/models/t5_film_transformer.py
* improvement: add type hints to src/diffusers/models/unet_1d_blocks.py
* improvement: add missing type hints to src/diffusers/models/unet_2d_blocks.py
* fix: CI error (make fix-copies required)
* fix: CI error (make fix-copies required again)
---------
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
* Add a new community pipeline
examples/community/latent_consistency_img2img.py
which can be called like this
import torch
from diffusers import DiffusionPipeline
pipe = DiffusionPipeline.from_pretrained(
"SimianLuo/LCM_Dreamshaper_v7", custom_pipeline="latent_consistency_txt2img", custom_revision="main")
# To save GPU memory, torch.float16 can be used, but it may compromise image quality.
pipe.to(torch_device="cuda", torch_dtype=torch.float32)
img2img=LatentConsistencyModelPipeline_img2img(
vae=pipe.vae,
text_encoder=pipe.text_encoder,
tokenizer=pipe.tokenizer,
unet=pipe.unet,
#scheduler=pipe.scheduler,
scheduler=None,
safety_checker=None,
feature_extractor=pipe.feature_extractor,
requires_safety_checker=False,
)
img = Image.open("thisismyimage.png")
result = img2img(prompt,img,strength,num_inference_steps=4)
* Apply suggestions from code review
Fix name formatting for scheduler
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* update readme (and run formatter on latent_consistency_img2img.py)
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* fix
* fix copies
* remove heun from tests
* add back heun and fix the tests to include 2nd order
* fix the other test too
* Apply suggestions from code review
* Apply suggestions from code review
* Apply suggestions from code review
* make style
* add more comments
---------
Co-authored-by: yiyixuxu <yixu310@gmail,com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* initial commit for LatentConsistencyModelPipeline and LCMScheduler based on the community pipeline
* Add callback and freeu support.
* apply suggestions from review
* Clean up LCMScheduler
* Remove timeindex argument to LCMScheduler.step.
* Add support for clipping or thresholding the predicted original sample.
* Remove unused methods and arguments in LCMScheduler.
* Improve comment about (lack of) negative prompt support.
* Change input guidance_scale to match the StableDiffusionPipeline (Imagen) CFG formulation.
* Move lcm_origin_steps from pipeline __call__ to LCMScheduler.__init__/config (as origin_steps).
* Fix typo when clipping/thresholding in LCMScheduler.
* Add some initial LCMScheduler tests.
* add type annotations from review
* Fix type annotation bug.
* Override test_add_noise_device in LCMSchedulerTest since hardcoded timesteps doesn't work under default settings.
* Add generator argument pipeline prepare_latents call.
* Cast LCMScheduler.timesteps to long in set_timesteps.
* Add onestep and multistep full loop scheduler tests.
* Set default height/width to None and don't hardcode guidance scale embedding dim.
* Add initial LatentConsistencyPipeline fast and slow tests.
* Add initial documentation for LatentConsistencyModelPipeline and LCMScheduler.
* Make remaining failing fast tests pass.
* make style
* Make original_inference_steps configurable from pipeline __call__ again.
* make style
* Remove guidance_rescale arg from pipeline __call__ since LCM currently doesn't support CFG.
* Make LCMScheduler defaults match config of LCM_Dreamshaper_v7 checkpoint.
* Fix LatentConsistencyPipeline slow tests and add dummy expected slices.
* Add checks for original_steps in LCMScheduler.set_timesteps.
* make fix-copies
* Improve LatentConsistencyModelPipeline docs.
* Apply suggestions from code review
Co-authored-by: Aryan V S <avs050602@gmail.com>
* Apply suggestions from code review
Co-authored-by: Aryan V S <avs050602@gmail.com>
* Apply suggestions from code review
Co-authored-by: Aryan V S <avs050602@gmail.com>
* Update src/diffusers/schedulers/scheduling_lcm.py
* Apply suggestions from code review
Co-authored-by: Aryan V S <avs050602@gmail.com>
* finish
---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Aryan V S <avs050602@gmail.com>
* add
* Update docs/source/en/api/pipelines/controlnet_sdxl.md
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
---------
Co-authored-by: yiyixuxu <yixu310@gmail,com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update get_dummy_inputs(...) in T2I-Adapter tests to take image height and width as params.
* Update the T2I-Adapter unit tests to run with the standard number of UNet down blocks so that all T2I-Adapter down blocks get exercised.
* Update the T2I-Adapter down blocks to better match the padding behavior of the UNet.
* Revert "Update the T2I-Adapter unit tests to run with the standard number of UNet down blocks so that all T2I-Adapter down blocks get exercised."
This reverts commit 6d4a060a34.
* Create utility functions for testing the T2I-Adapter downscaling bahevior.
* (minor) Improve readability with an intermediate named variable.
* Statically parameterize T2I-Adapter test dimensions rather than generating them dynamically.
* Fix static checks.
---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* Added args, kwargs to ```U
* Add UNetMidBlock2D as a supported mid block type
* Fix extra init input for UNetMidBlock2D, change allowed types for Mid-block init
* Update unet_2d_condition.py
* Update unet_2d_condition.py
* Update unet_2d_condition.py
* Update unet_2d_condition.py
* Update unet_2d_condition.py
* Update unet_2d_condition.py
* Update unet_2d_condition.py
* Update unet_2d_condition.py
* Update unet_2d_blocks.py
* Update unet_2d_blocks.py
* Update unet_2d_blocks.py
* Update unet_2d_condition.py
* Update unet_2d_blocks.py
* Updated docstring, increased check strictness
Updated the docstring for ```UNet2DConditionModel``` to include ```reverse_transformer_layers_per_block``` and updated checking for nested list type ```transformer_layers_per_block```
* Add basic shape-check test for asymmetrical unets
* Update src/diffusers/models/unet_2d_blocks.py
Removed blank line
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* Update unet_2d_condition.py
Remove blank space
* Update unet_2d_condition.py
Changed docstring for `mid_block_type`
* Fixed docstring and wrong default value
* Reformat with black
* Reformat with necessary commands
* Add UNetMidBlockFlat to versatile_diffusion/modeling_text_unet.py to ensure consistency
* Removed args, kwargs, use on mid-block type
* Make fix-copies
* Update src/diffusers/models/unet_2d_condition.py
Wrap into single line
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* make fix-copies
---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* 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.
* Update unet_2d_blocks.py
Added Beutifull doc-string into the UNetMidBlock2D class.
* Update unet_2d_blocks.py
I replaced the definition in this parameter resnet_time_scale_shift and resnet_groups.
* Update unet_2d_blocks.py
I remove additional sentences into the resnet_groups argument.
* Update unet_2d_blocks.py
I replaced my definition with the maintainer definition in the attention_head_dim parameter.
* I am using black package for reformated my file
---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>
* added TODOs
* Enhanced and reformatted the docstrings of IFPipeline methods.
* Enhanced and fixed the docstrings of IFImg2ImgSuperResolutionPipeline methods.
* Enhanced and fixed the docstrings of IFImg2ImgPipeline methods.
* Enhanced and fixed the docstrings of IFInpaintingSuperResolutionPipeline methods.
* Enhanced and fixed the docstrings of IFInpaintingPipeline methods.
* Enhanced and fixed the docstrings of IFSuperResolutionPipeline methods.
* Update src/diffusers/pipelines/deepfloyd_if/pipeline_if.py
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update src/diffusers/pipelines/deepfloyd_if/pipeline_if_img2img.py
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update src/diffusers/pipelines/deepfloyd_if/pipeline_if_img2img_superresolution.py
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update src/diffusers/pipelines/deepfloyd_if/pipeline_if_inpainting.py
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update src/diffusers/pipelines/deepfloyd_if/pipeline_if_superresolution.py
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update src/diffusers/pipelines/deepfloyd_if/pipeline_if_inpainting_superresolution.py
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* remove redundant code
* fix code style
* revert the ordering to not break backwards compatibility
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* changed channel parameters for UNET and VAE. Decreased hidden layers size with increased attention heads and intermediate size
* changed the assertion check range
* clean up
---------
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
* fix: sdxl pipeline when unet is not available.
* fix moe
* account for text
* ifx more
* don't make unet optional.
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* split conditionals.
* add optional components to sdxl pipeline
* propagate changes to the rest of the pipelines.
* add: test
* add to all
* fix: rest of the pipelines.
* use pipeline_class variable
* separate pipeline mixin
* use safe_serialization
* fix: test
* access actual output.
* add: optional test to adapter and ip2p sdxl pipeline tests/
* add optional test to controlnet sdxl.
* fix tests
* fix ip2p tests
* fix more
* fifx more.
* use np output type.
* fix for StableDiffusionXLMultiControlNetPipelineFastTests.
* fix: SDXLOptionalComponentsTesterMixin
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* fix tests
* Empty-Commit
* revert previous
* quality
* fix: test
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Add ability to mix usage of T2I-Adapter(s) and ControlNet(s).
Previously, UNet2DConditional implemnetation onloy allowed use of one or the other.
Adds new forward() arg down_intrablock_additional_residuals specifically for T2I-Adapters. If down_intrablock_addtional_residuals is not used, maintains backward compatibility with prior usage of only T2I-Adapter or ControlNet but not both
* Improving forward() arg docs in src/diffusers/models/unet_2d_condition.py
Co-authored-by: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
* Add deprecation warning if down_block_additional_residues is used for T2I-Adapter (intrablock residuals)
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Oops my bad, fixing last commit.
* Added import of diffusers utils.deprecate
* Conform to max line length
* Modifying T2I-Adapter pipelines to reflect change to UNet forward() arg for T2I-Adapter residuals.
---------
Co-authored-by: psychedelicious <4822129+psychedelicious@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
