GitLab

* fix some typo error

* Undo changes to capitalization

* controlnet sd 2.1 checkpoint conversions

* remove global_step -> make config file mandatory

* [From pretrained] Speed-up loading from cache

* up

* Fix more

* fix one more bug

* make style

* bigger refactor

* factor out function

* Improve more

* better

* deprecate return cache folder

* clean up

* improve tests

* up

* upload

* add nice tests

* simplify

* finish

* correct

* fix version

* rename

* Apply suggestions from code review
Co-authored-by: Lucain <lucainp@gmail.com>

* rename

* correct doc string

* correct more

* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* apply code suggestions

* finish

---------
Co-authored-by: Lucain <lucainp@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>

* 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>

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

* convert __main__ to a function call and call it

* add missing type hint

* make style check pass

* move loading to src/diffusers
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

Fix unused upcast_attn flag in sd to diffusers script

* [Conversion] Make sure ema weights are extracted correctly

* up

* finish

* Device to use (e.g. cpu, cuda:0, cuda:1, etc.)

* "cuda" if torch.cuda.is_available() else "cpu"

handle missing global_step key and don't download config if it already exists

* Initial code for attempt at improving SD <--> diffusers conversions for v2.0

* Updates to support round-trip between orig. SD 2.0 and diffusers models

* Corrected formatting to Black standard

* Correcting import formatting

* Fixed imports (properly this time)

* add some corrections

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

* add paint by example

* mkae loading possibel

* up

* Update src/diffusers/models/attention.py

* up

* finalize weight structure

* make example work

* make it work

* up

* up

* fix

* del

* add

* update

* Apply suggestions from code review

* correct transformer 2d

* finish

* up

* up

* up

* up

* fix

* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Apply suggestions from code review

* up

* finish
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Conversion SD 2

* finish

* Add an explicit `--image_size` to the conversion script

* style

up

up

CompVis -> diffusers script - allow converting from merged checkpoint to either EMA or non-EMA (#991)

* improve script

* up

* begin text2img conversion script

* add fn to convert config

* create config if not provided

* update imports and use UNet2DConditionModel

* fix imports, layer names

* fix unet coversion

* add function to convert VAE

* fix vae conversion

* update main

* create text model

* update config creating logic for unet

* fix config creation

* update script to create and save pipeline

* remove unused imports

* fix checkpoint loading

* better name

* save progress

* finish

* up

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