The 'CLIPFeatureExtractor' class name has been renamed to 'CLIPImageProcessor' in order to comply with future deprecation. This commit includes the necessary changes to the affected files.
* [MS Text To Video} Add first text to video
* upload
* make first model example
* match unet3d params
* make sure weights are correcctly converted
* improve
* forward pass works, but diff result
* make forward work
* fix more
* finish
* refactor video output class.
* feat: add support for a video export utility.
* fix: opencv availability check.
* run make fix-copies.
* add: docs for the model components.
* add: standalone pipeline doc.
* edit docstring of the pipeline.
* add: right path to TransformerTempModel
* add: first set of tests.
* complete fast tests for text to video.
* fix bug
* up
* three fast tests failing.
* add: note on slow tests
* make work with all schedulers
* apply styling.
* add slow tests
* change file name
* update
* more correction
* more fixes
* finish
* up
* Apply suggestions from code review
* up
* finish
* make copies
* fix pipeline tests
* fix more tests
* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* apply suggestions
* up
* revert
---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Add support for different model prediction types in DDIMInverseScheduler
Resolve alpha_prod_t_prev index issue for final step of inversion
* Fix old bug introduced when prediction type is "sample"
* Add support for sample clipping for numerical stability and deprecate old kwarg
* Detach sample, alphas, betas
Derive predicted noise from model output before dist. regularization
Style cleanup
* Log loss for debugging
* Revert "Log loss for debugging"
This reverts commit 76ea9c856f99f4c8eca45a0b1801593bb982584b.
* Add comments
* Add inversion equivalence test
* Add expected data for Pix2PixZero pipeline tests with SD 2
* Update tests/pipelines/stable_diffusion/test_stable_diffusion_pix2pix_zero.py
* Remove cruft and add more explanatory comments
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* support for List[ControlNetModel] on init()
* Add to support for multiple ControlNetCondition
* rename conditioning_scale to scale
* scaling bugfix
* Manually merge `MultiControlNet` #2621
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_controlnet.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_controlnet.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_controlnet.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_controlnet.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_controlnet.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_controlnet.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* cleanups
- don't expose ControlNetCondition
- move scaling to ControlNetModel
* make style error correct
* remove ControlNetCondition to reduce code diff
* refactoring image/cond_scale
* add explain for `images`
* Add docstrings
* all fast-test passed
* Add a slow test
* nit
* Apply suggestions from code review
* small precision fix
* nits
MultiControlNet -> MultiControlNetModel - Matches existing naming a bit
closer
MultiControlNetModel inherit from model utils class - Don't have to
re-write fp16 test
Skip tests that save multi controlnet pipeline - Clearer than changing
test body
Don't auto-batch the number of input images to the number of controlnets.
We generally like to require the user to pass the expected number of
inputs. This simplifies the processing code a bit more
Use existing image pre-processing code a bit more. We can rely on the
existing image pre-processing code and keep the inference loop a bit
simpler.
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: William Berman <WLBberman@gmail.com>
* [Onnx] add Stable Diffusion Upscale pipeline
* add a test for the OnnxStableDiffusionUpscalePipeline
* check for VAE config before adjusting scaling factor
* update test assertions, lint fixes
* run fix-copies target
* switch test checkpoint to one hosted on huggingface
* partially restore attention mask
* reshape embeddings after running text encoder
* add longer nightly test for ONNX upscale pipeline
* use package import to fix tests
* fix scheduler compatibility and class labels dtype
* use more precise type
* remove LMS from fast tests
* lookup latent and timestamp types
* add docs for ONNX upscaling, rename lookup table
* replace deprecated pipeline names in ONNX docs
* 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>
* Skip variant tests (UNet1d, UNetRL) on mps.
mish op not yet supported.
* Exclude a couple of panorama tests on mps
They are too slow for fast CI.
* Exclude mps panorama from more tests.
* mps: exclude all fast panorama tests as they keep failing.
* 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>
* unet check length input
* prep test file for changes
* correct all tests
* clean up
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Kashif Rasul