* Fix the XL ensemble not working for any kerras scheduler sigmas and having an off by one bug
* Update src/diffusers/pipelines/stable_diffusion_xl/pipeline_stable_diffusion_xl.py
* make sytle
---------
Co-authored-by: Jimmy <39@🇺🇸.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Quick implementation of t2i-adapter
Load adapter module with from_pretrained
Prototyping generalized adapter framework
Writeup doc string for sideload framework(WIP) + some minor update on implementation
Update adapter models
Remove old adapter optional args in UNet
Add StableDiffusionAdapterPipeline unit test
Handle cpu offload in StableDiffusionAdapterPipeline
Auto correct coding style
Update model repo name to "RzZ/sd-v1-4-adapter-pipeline"
Refactor MultiAdapter to better compatible with config system
Export MultiAdapter
Create pipeline document template from controlnet
Create dummy objects
Supproting new AdapterLight model
Fix StableDiffusionAdapterPipeline common pipeline test
[WIP] Update adapter pipeline document
Handle num_inference_steps in StableDiffusionAdapterPipeline
Update definition of Adapter "channels_in"
Update documents
Apply code style
Fix doc typo and merge error
Update doc string and example
Quality of life improvement
Remove redundant code and file from prototyping
Remove unused pageage
Remove comments
Fix title
Fix typo
Add conditioning scale arg
Bring back old implmentation
Offload sideload
Add supply info on document
Update src/diffusers/models/adapter.py
Co-authored-by: Will Berman <wlbberman@gmail.com>
Update MultiAdapter constructor
Swap out custom checkpoint and update pipeline constructor
Update docment
Apply suggestions from code review
Co-authored-by: Will Berman <wlbberman@gmail.com>
Correcting style
Following single-file policy
Update auto size in image preprocess func
Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_adapter.py
Co-authored-by: Will Berman <wlbberman@gmail.com>
fix copies
Update adapter pipeline behavior
Add adapter_conditioning_scale doc string
Add the missing doc string
Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Fix few bugs from suggestion
Handle L-mode PIL image as control image
Rename to differentiate adapter resblock
Update src/diffusers/models/adapter.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Fix typo
Update adapter parameter name
Update test case and code style
Fix copies
Fix typo
Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_adapter.py
Co-authored-by: Will Berman <wlbberman@gmail.com>
Update Adapter class name
Add checkpoint converting script
Fix style
Fix-copies
Remove dev script
Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Updates for parameter rename
Fix convert_adapter
remove main
fix diff
more
refactoring
more
more
small fixes
refactor
tests
more slow tests
more tests
Update docs/source/en/api/pipelines/overview.mdx
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
add community contributor to docs
Update docs/source/en/api/pipelines/stable_diffusion/adapter.mdx
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Update docs/source/en/api/pipelines/stable_diffusion/adapter.mdx
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Update docs/source/en/api/pipelines/stable_diffusion/adapter.mdx
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Update docs/source/en/api/pipelines/stable_diffusion/adapter.mdx
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Update docs/source/en/api/pipelines/stable_diffusion/adapter.mdx
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
fix
remove from_adapters
license
paper link
docs
more url fixes
more docs
fix
fixes
fix
fix
* fix sample inplace add
* additional_kwargs -> additional_residuals
* move t2i adapter pipeline to own module
* preprocess -> _preprocess_adapter_image
* add TencentArc to license
* fix example code links
* add image converter and fix example doc string
* fix links
* clearer additional residual application
---------
Co-authored-by: HimariO <dsfhe49854@gmail.com>
* diffusers#4003 - initial implementation of max_inference_steps
* diffusers#4003 - initial implementation of max_inference_steps and first_inference_step for img2img
* diffusers#4003 - use first_inference_step as an input arg for get_timestamps in img2img
* diffusers#4003 Do not add noise during img2img when we have a defined first timestep
* diffusers#4003 Mild updates after revert
* diffusers#4003 Missing change
* Show implementation with denoising_start and end
* Apply suggestions from code review
* Update src/diffusers/pipelines/stable_diffusion_xl/pipeline_stable_diffusion_xl.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* move to 0.19.0dev
* Apply suggestions from code review
* add exhaustive tests
* add docs
* finish
* Apply suggestions from code review
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* make style
---------
Co-authored-by: bghira <bghira@users.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* Add new text encoder
* add transformers depth
* More
* Correct conversion script
* Fix more
* Fix more
* Correct more
* correct text encoder
* Finish all
* proof that in works in run local xl
* clean up
* Get refiner to work
* Add red castle
* Fix batch size
* Improve pipelines more
* Finish text2image tests
* Add img2img test
* Fix more
* fix import
* Fix embeddings for classic models (#3888)
Fix embeddings for classic SD models.
* Allow multiple prompts to be passed to the refiner (#3895)
* finish more
* Apply suggestions from code review
* add watermarker
* Model offload (#3889)
* Model offload.
* Model offload for refiner / img2img
* Hardcode encoder offload on img2img vae encode
Saves some GPU RAM in img2img / refiner tasks so it remains below 8 GB.
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* correct
* fix
* clean print
* Update install warning for `invisible-watermark`
* add: missing docstrings.
* fix and simplify the usage example in img2img.
* fix setup for watermarking.
* Revert "fix setup for watermarking."
This reverts commit 491bc9f5a6.
* fix: watermarking setup.
* fix: op.
* run make fix-copies.
* make sure tests pass
* improve convert
* make tests pass
* make tests pass
* better error message
* fiinsh
* finish
* Fix final test
---------
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* add entry for safe stable diffusion to the sd overview page.
* add missing pipelines o the broader overview section in the pipelines.
* address PR feedback./
* added ldm3d pipeline and updated image processor to support depth
* added description
* added paper reference
* added docs
* fixed bug
* added test
* Update tests/pipelines/stable_diffusion/test_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update tests/pipelines/stable_diffusion/test_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* added reference in indexmdx
* reverted changes tto image processor'
* added LDM3DOutput
* Fixes with make style
* fix failing tests for make fix-copies
* aligned with our version
* Update pipeline_stable_diffusion_ldm3d.py
updated the guidance scale
* Fix for failing check_code_quality test
* Code review feedback
* Fix typo in ldm3d_diffusion.mdx
* updated the doc accordnlgy
* copyrights
* fixed test failure
* make style
* added image processor of LDM3D in the documentation:
* added ldm3d doc to toctree
* run make style && make quality
* run make fix-copies
* Update docs/source/en/api/image_processor.mdx
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* Update docs/source/en/api/pipelines/stable_diffusion/ldm3d_diffusion.mdx
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* Update docs/source/en/api/pipelines/stable_diffusion/ldm3d_diffusion.mdx
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* updated the safety checker to accept tuple
* make style and make quality
* Update src/diffusers/pipelines/stable_diffusion/__init__.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* LDM3D output
* up
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Aflalo <estellea@isl-gpu27.rr.intel.com>
Co-authored-by: Anahita Bhiwandiwalla <anahita.bhiwandiwalla@intel.com>
Co-authored-by: Aflalo <estellea@isl-gpu26.rr.intel.com>
Co-authored-by: Aflalo <estellea@isl-iam1.rr.intel.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Aflalo <estellea@isl-gpu42.rr.intel.com>
Co-authored-by: Aflalo <estellea@isl-gpu43.rr.intel.com>
* Implement option for rescaling betas to zero terminal SNR
* Implement rescale classifier free guidance in pipeline_stable_diffusion.py
* focus on DDIM
* make style
* make style
* make style
* make style
* Apply suggestions from Peter Lin
* Apply suggestions from Peter Lin
* make style
* Apply suggestions from code review
* Apply suggestions from code review
* make style
* make style
---------
Co-authored-by: MaxWe00 <gitlab.9v1lq@slmail.me>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* refactor controlnet and add img2img and inpaint
* First draft to get pipelines to work
* make style
* Fix more
* Fix more
* More tests
* Fix more
* Make inpainting work
* make style and more tests
* Apply suggestions from code review
* up
* make style
* Fix imports
* Fix more
* Fix more
* Improve examples
* add test
* Make sure import is correctly deprecated
* Make sure everything works in compile mode
* make sure authorship is correctly attributed
* Update Pix2PixZero Auto-correlation Loss
* Add Stable Diffusion DiffEdit pipeline
* Add draft documentation and import code
* Bugfixes and refactoring
* Add option to not decode latents in the inversion process
* Harmonize preprocessing
* Revert "Update Pix2PixZero Auto-correlation Loss"
This reverts commit b218062fed.
* Update annotations
* rename `compute_mask` to `generate_mask`
* Update documentation
* Update docs
* Update Docs
* Fix copy
* Change shape of output latents to batch first
* Update docs
* Add first draft for tests
* Bugfix and update tests
* Add `cross_attention_kwargs` support for all pipeline methods
* Fix Copies
* Add support for PIL image latents
Add support for mask broadcasting
Update docs and tests
Align `mask` argument to `mask_image`
Remove height and width arguments
* Enable MPS Tests
* Move example docstrings
* Fix test
* Fix test
* fix pipeline inheritance
* Harmonize `prepare_image_latents` with StableDiffusionPix2PixZeroPipeline
* Register modules set to `None` in config for `test_save_load_optional_components`
* Move fixed logic to specific test class
* Clean changes to other pipelines
* Update new tests to coordinate with #2953
* Update slow tests for better results
* Safety to avoid potential problems with torch.inference_mode
* Add reference in SD Pipeline Overview
* Fix tests again
* Enforce determinism in noise for generate_mask
* Fix copies
* Widen test tolerance for fp16 based on `test_stable_diffusion_upscale_pipeline_fp16`
* Add LoraLoaderMixin and update `prepare_image_latents`
* clean up repeat and reg
* bugfix
* Remove invalid args from docs
Suppress spurious warning by repeating image before latent to mask gen
* add mixin class for pipeline from original sd ckpt
* Improve
* make style
* merge main into
* Improve more
* fix more
* up
* Apply suggestions from code review
* finish docs
* rename
* make style
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* add guess mode (WIP)
* fix uncond/cond order
* support guidance_scale=1.0 and batch != 1
* remove magic coeff
* add docstring
* add intergration test
* add document to controlnet.mdx
* made the comments a bit more explanatory
* fix table
* Tiled VAE for high-res text2img and img2img
* vae tiling, fix formatting
* enable_vae_tiling API and tests
* tiled vae docs, disable tiling for images that would have only one tile
* tiled vae tests, use channels_last memory format
* tiled vae tests, use smaller test image
* tiled vae tests, remove tiling test from fast tests
* up
* up
* make style
* Apply suggestions from code review
* Apply suggestions from code review
* Apply suggestions from code review
* make style
* improve naming
* finish
* apply suggestions
* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* up
---------
Co-authored-by: Ilmari Heikkinen <ilmari@fhtr.org>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* add scaffold
- copied convert_controlnet_to_diffusers.py from
convert_original_stable_diffusion_to_diffusers.py
* Add support to load ControlNet (WIP)
- this makes Missking Key error on ControlNetModel
* Update to convert ControlNet without error msg
- init impl for StableDiffusionControlNetPipeline
- init impl for ControlNetModel
* cleanup of commented out
* split create_controlnet_diffusers_config()
from create_unet_diffusers_config()
- add config: hint_channels
* Add input_hint_block, input_zero_conv and
middle_block_out
- this makes missing key error on loading model
* add unet_2d_blocks_controlnet.py
- copied from unet_2d_blocks.py as impl CrossAttnDownBlock2D,DownBlock2D
- this makes missing key error on loading model
* Add loading for input_hint_block, zero_convs
and middle_block_out
- this makes no error message on model loading
* Copy from UNet2DConditionalModel except __init__
* Add ultra primitive test for ControlNetModel
inference
* Support ControlNetModel inference
- without exceptions
* copy forward() from UNet2DConditionModel
* Impl ControlledUNet2DConditionModel inference
- test_controlled_unet_inference passed
* Frozen weight & biases for training
* Minimized version of ControlNet/ControlledUnet
- test_modules_controllnet.py passed
* make style
* Add support model loading for minimized ver
* Remove all previous version files
* from_pretrained and inference test passed
* copied from pipeline_stable_diffusion.py
except `__init__()`
* Impl pipeline, pixel match test (almost) passed.
* make style
* make fix-copies
* Fix to add import ControlNet blocks
for `make fix-copies`
* Remove einops dependency
* Support np.ndarray, PIL.Image for controlnet_hint
* set default config file as lllyasviel's
* Add support grayscale (hw) numpy array
* Add and update docstrings
* add control_net.mdx
* add control_net.mdx to toctree
* Update copyright year
* Fix to add PIL.Image RGB->BGR conversion
- thanks @Mystfit
* make fix-copies
* add basic fast test for controlnet
* add slow test for controlnet/unet
* Ignore down/up_block len check on ControlNet
* add a copy from test_stable_diffusion.py
* Accept controlnet_hint is None
* merge pipeline_stable_diffusion.py diff
* Update class name to SDControlNetPipeline
* make style
* Baseline fast test almost passed (w long desc)
* still needs investigate.
Following didn't passed descriped in TODO comment:
- test_stable_diffusion_long_prompt
- test_stable_diffusion_no_safety_checker
Following didn't passed same as stable_diffusion_pipeline:
- test_attention_slicing_forward_pass
- test_inference_batch_single_identical
- test_xformers_attention_forwardGenerator_pass
these seems come from calc accuracy.
* Add note comment related vae_scale_factor
* add test_stable_diffusion_controlnet_ddim
* add assertion for vae_scale_factor != 8
* slow test of pipeline almost passed
Failed: test_stable_diffusion_pipeline_with_model_offloading
- ImportError: `enable_model_offload` requires `accelerate v0.17.0` or higher
but currently latest version == 0.16.0
* test_stable_diffusion_long_prompt passed
* test_stable_diffusion_no_safety_checker passed
- due to its model size, move to slow test
* remove PoC test files
* fix num_of_image, prompt length issue add add test
* add support List[PIL.Image] for controlnet_hint
* wip
* all slow test passed
* make style
* update for slow test
* RGB(PIL)->BGR(ctrlnet) conversion
* fixes
* remove manual num_images_per_prompt test
* add document
* add `image` argument docstring
* make style
* Add line to correct conversion
* add controlnet_conditioning_scale (aka control_scales
strength)
* rgb channel ordering by default
* image batching logic
* Add control image descriptions for each checkpoint
* Only save controlnet model in conversion script
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_controlnet.py
typo
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update docs/source/en/api/pipelines/stable_diffusion/control_net.mdx
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update docs/source/en/api/pipelines/stable_diffusion/control_net.mdx
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update docs/source/en/api/pipelines/stable_diffusion/control_net.mdx
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update docs/source/en/api/pipelines/stable_diffusion/control_net.mdx
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update docs/source/en/api/pipelines/stable_diffusion/control_net.mdx
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update docs/source/en/api/pipelines/stable_diffusion/control_net.mdx
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update docs/source/en/api/pipelines/stable_diffusion/control_net.mdx
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update docs/source/en/api/pipelines/stable_diffusion/control_net.mdx
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update docs/source/en/api/pipelines/stable_diffusion/control_net.mdx
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* add gerated image example
* a depth mask -> a depth map
* rename control_net.mdx to controlnet.mdx
* fix toc title
* add ControlNet abstruct and link
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_controlnet.py
Co-authored-by: dqueue <dbyqin@gmail.com>
* remove controlnet constructor arguments re: @patrickvonplaten
* [integration tests] test canny
* test_canny fixes
* [integration tests] test_depth
* [integration tests] test_hed
* [integration tests] test_mlsd
* add channel order config to controlnet
* [integration tests] test normal
* [integration tests] test_openpose test_scribble
* change height and width to default to conditioning image
* [integration tests] test seg
* style
* test_depth fix
* [integration tests] size fixes
* [integration tests] cpu offloading
* style
* generalize controlnet embedding
* fix conversion script
* Update docs/source/en/api/pipelines/stable_diffusion/controlnet.mdx
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* Update docs/source/en/api/pipelines/stable_diffusion/controlnet.mdx
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* Update docs/source/en/api/pipelines/stable_diffusion/controlnet.mdx
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* Update docs/source/en/api/pipelines/stable_diffusion/controlnet.mdx
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* Style adapted to the documentation of pix2pix
* merge main by hand
* style
* [docs] controlling generation doc nits
* correct some things
* add: controlnetmodel to autodoc.
* finish docs
* finish
* finish 2
* correct images
* finish controlnet
* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* uP
* upload model
* up
* up
---------
Co-authored-by: William Berman <WLBberman@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: dqueue <dbyqin@gmail.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* attend and excite pipeline
* update
update docstring example
remove visualization
remove the base class attention control
remove dependency on stable diffusion pipeline
always apply gaussian filter with default setting
remove run_standard_sd argument
hardcode attention_res and scale_range (related to step size)
Update docs/source/en/api/pipelines/stable_diffusion/attend_and_excite.mdx
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_attend_and_excite.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_attend_and_excite.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_attend_and_excite.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_attend_and_excite.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_attend_and_excite.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_attend_and_excite.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Update tests/pipelines/stable_diffusion_2/test_stable_diffusion_attend_and_excite.py
Co-authored-by: Will Berman <wlbberman@gmail.com>
Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_attend_and_excite.py
Co-authored-by: Will Berman <wlbberman@gmail.com>
Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_attend_and_excite.py
Co-authored-by: Will Berman <wlbberman@gmail.com>
revert test_float16_inference
revert change to the batch related tests
fix test_float16_inference
handle batch
remove the deprecation message
remove None check, step_size
remove debugging logging
add slow test
indices_to_alter -> indices
add check_input
* skip mps
* style
* Apply suggestions from code review
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* indices -> token_indices
---------
Co-authored-by: evin <evinpinarornek@gmail.com>
Co-authored-by: yiyixuxu <yixu310@gmail,com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* add: support for BLIP generation.
* add: support for editing synthetic images.
* remove unnecessary comments.
* add inits and run make fix-copies.
* version change of diffusers.
* fix: condition for loading the captioner.
* default conditions_input_image to False.
* guidance_amount -> cross_attention_guidance_amount
* fix inputs to check_inputs()
* fix: attribute.
* fix: prepare_attention_mask() call.
* debugging.
* better placement of references.
* remove torch.no_grad() decorations.
* put torch.no_grad() context before the first denoising loop.
* detach() latents before decoding them.
* put deocding in a torch.no_grad() context.
* add reconstructed image for debugging.
* no_grad(0
* apply formatting.
* address one-off suggestions from the draft PR.
* back to torch.no_grad() and add more elaborate comments.
* refactor prepare_unet() per Patrick's suggestions.
* more elaborate description for .
* formatting.
* add docstrings to the methods specific to pix2pix zero.
* suspecting a redundant noise prediction.
* needed for gradient computation chain.
* less hacks.
* fix: attention mask handling within the processor.
* remove attention reference map computation.
* fix: cross attn args.
* fix: prcoessor.
* store attention maps.
* fix: attention processor.
* update docs and better treatment to xa args.
* update the final noise computation call.
* change xa args call.
* remove xa args option from the pipeline.
* add: docs.
* first test.
* fix: url call.
* fix: argument call.
* remove image conditioning for now.
* 🚨 add: fast tests.
* explicit placement of the xa attn weights.
* add: slow tests 🐢
* fix: tests.
* edited direction embedding should be on the same device as prompt_embeds.
* debugging message.
* debugging.
* add pix2pix zero pipeline for a non-deterministic test.
* debugging/
* remove debugging message.
* make caption generation _
* address comments (part I).
* address PR comments (part II)
* fix: DDPM test assertion.
* refactor doc.
* address PR comments (part III).
* fix: type annotation for the scheduler.
* apply styling.
* skip_mps and add note on embeddings in the docs.
* pipeline_variant
* Add docs for when clip_stats_path is specified
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_unclip.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_unclip.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_unclip_img2img.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_unclip_img2img.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* prepare_latents # Copied from re: @patrickvonplaten
* NoiseAugmentor->ImageNormalizer
* stable_unclip_prior default to None re: @patrickvonplaten
* prepare_prior_extra_step_kwargs
* prior denoising scale model input
* {DDIM,DDPM}Scheduler -> KarrasDiffusionSchedulers re: @patrickvonplaten
* docs
* Update docs/source/en/api/pipelines/stable_unclip.mdx
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Modify UNet2DConditionModel
- allow skipping mid_block
- adding a norm_group_size argument so that we can set the `num_groups` for group norm using `num_channels//norm_group_size`
- allow user to set dimension for the timestep embedding (`time_embed_dim`)
- the kernel_size for `conv_in` and `conv_out` is now configurable
- add random fourier feature layer (`GaussianFourierProjection`) for `time_proj`
- allow user to add the time and class embeddings before passing through the projection layer together - `time_embedding(t_emb + class_label))`
- added 2 arguments `attn1_types` and `attn2_types`
* currently we have argument `only_cross_attention`: when it's set to `True`, we will have a to the
`BasicTransformerBlock` block with 2 cross-attention , otherwise we
get a self-attention followed by a cross-attention; in k-upscaler, we need to have blocks that include just one cross-attention, or self-attention -> cross-attention;
so I added `attn1_types` and `attn2_types` to the unet's argument list to allow user specify the attention types for the 2 positions in each block; note that I stil kept
the `only_cross_attention` argument for unet for easy configuration, but it will be converted to `attn1_type` and `attn2_type` when passing down to the down blocks
- the position of downsample layer and upsample layer is now configurable
- in k-upscaler unet, there is only one skip connection per each up/down block (instead of each layer in stable diffusion unet), added `skip_freq = "block"` to support
this use case
- if user passes attention_mask to unet, it will prepare the mask and pass a flag to cross attention processer to skip the `prepare_attention_mask` step
inside cross attention block
add up/down blocks for k-upscaler
modify CrossAttention class
- make the `dropout` layer in `to_out` optional
- `use_conv_proj` - use conv instead of linear for all projection layers (i.e. `to_q`, `to_k`, `to_v`, `to_out`) whenever possible. note that when it's used to do cross
attention, to_k, to_v has to be linear because the `encoder_hidden_states` is not 2d
- `cross_attention_norm` - add an optional layernorm on encoder_hidden_states
- `attention_dropout`: add an optional dropout on attention score
adapt BasicTransformerBlock
- add an ada groupnorm layer to conditioning attention input with timestep embedding
- allow skipping the FeedForward layer in between the attentions
- replaced the only_cross_attention argument with attn1_type and attn2_type for more flexible configuration
update timestep embedding: add new act_fn gelu and an optional act_2
modified ResnetBlock2D
- refactored with AdaGroupNorm class (the timestep scale shift normalization)
- add `mid_channel` argument - allow the first conv to have a different output dimension from the second conv
- add option to use input AdaGroupNorm on the input instead of groupnorm
- add options to add a dropout layer after each conv
- allow user to set the bias in conv_shortcut (needed for k-upscaler)
- add gelu
adding conversion script for k-upscaler unet
add pipeline
* fix attention mask
* fix a typo
* fix a bug
* make sure model can be used with GPU
* make pipeline work with fp16
* fix an error in BasicTransfomerBlock
* make style
* fix typo
* some more fixes
* uP
* up
* correct more
* some clean-up
* clean time proj
* up
* uP
* more changes
* remove the upcast_attention=True from unet config
* remove attn1_types, attn2_types etc
* fix
* revert incorrect changes up/down samplers
* make style
* remove outdated files
* Apply suggestions from code review
* attention refactor
* refactor cross attention
* Apply suggestions from code review
* update
* up
* update
* Apply suggestions from code review
* finish
* Update src/diffusers/models/cross_attention.py
* more fixes
* up
* up
* up
* finish
* more corrections of conversion state
* act_2 -> act_2_fn
* remove dropout_after_conv from ResnetBlock2D
* make style
* simplify KAttentionBlock
* add fast test for latent upscaler pipeline
* add slow test
* slow test fp16
* make style
* add doc string for pipeline_stable_diffusion_latent_upscale
* add api doc page for latent upscaler pipeline
* deprecate attention mask
* clean up embeddings
* simplify resnet
* up
* clean up resnet
* up
* correct more
* up
* up
* improve a bit more
* correct more
* more clean-ups
* Update docs/source/en/api/pipelines/stable_diffusion/latent_upscale.mdx
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update docs/source/en/api/pipelines/stable_diffusion/latent_upscale.mdx
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* add docstrings for new unet config
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_latent_upscale.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_latent_upscale.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* # Copied from
* encode the image if not latent
* remove force casting vae to fp32
* fix
* add comments about preconditioning parameters from k-diffusion paper
* attn1_type, attn2_type -> add_self_attention
* clean up get_down_block and get_up_block
* fix
* fixed a typo(?) in ada group norm
* update slice attention processer for cross attention
* update slice
* fix fast test
* update the checkpoint
* finish tests
* fix-copies
* fix-copy for modeling_text_unet.py
* make style
* make style
* fix f-string
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_latent_upscale.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* fix import
* correct changes
* fix resnet
* make fix-copies
* correct euler scheduler
* add missing #copied from for preprocess
* revert
* fix
* fix copies
* Update docs/source/en/api/pipelines/stable_diffusion/latent_upscale.mdx
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update docs/source/en/api/pipelines/stable_diffusion/latent_upscale.mdx
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update docs/source/en/api/pipelines/stable_diffusion/latent_upscale.mdx
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update docs/source/en/api/pipelines/stable_diffusion/latent_upscale.mdx
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update src/diffusers/models/cross_attention.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_latent_upscale.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_latent_upscale.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* clean up conversion script
* KDownsample2d,KUpsample2d -> KDownsample2D,KUpsample2D
* more
* Update src/diffusers/models/unet_2d_condition.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* remove prepare_extra_step_kwargs
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_latent_upscale.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_latent_upscale.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* fix a typo in timestep embedding
* remove num_image_per_prompt
* fix fasttest
* make style + fix-copies
* fix
* fix xformer test
* fix style
* doc string
* make style
* fix-copies
* docstring for time_embedding_norm
* make style
* final finishes
* make fix-copies
* fix tests
---------
Co-authored-by: yiyixuxu <yixu@yis-macbook-pro.lan>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
39th president of the United States, probably