* Add default to inpaint
* Make sure controlnet also works with normal sd for inpaint
* Add tests
* improve
* Correct encode images function
* Correct inpaint controlnet
* Improve text2img inpanit
* make style
* up
* up
* up
* up
* fix more
* Run ControlNet compile test in a separate subprocess
`torch.compile()` spawns several subprocesses and the GPU memory used
was not reclaimed after the test ran. This approach was taken from
`transformers`.
* Style
* Prepare a couple more compile tests to run in subprocess.
* Use require_torch_2 decorator.
* Test inpaint_compile in subprocess.
* Run img2img compile test in subprocess.
* Run stable diffusion compile test in subprocess.
* style
* Temporarily trigger on pr to test.
* Revert "Temporarily trigger on pr to test."
This reverts commit 82d76868dd.
* up
* fix more
* Apply suggestions from code review
* fix more
* fix more
* Check it
* Remove 16:8
* fix more
* fix more
* fix more
* up
* up
* Test only stable diffusion
* Test only two files
* up
* Try out spinning up processes that can be killed
* up
* Apply suggestions from code review
* up
* up
* Added explanation of 'strength' parameter
* Added get_timesteps function which relies on new strength parameter
* Added `strength` parameter which defaults to 1.
* Swapped ordering so `noise_timestep` can be calculated before masking the image
this is required when you aren't applying 100% noise to the masked region, e.g. strength < 1.
* Added strength to check_inputs, throws error if out of range
* Changed `prepare_latents` to initialise latents w.r.t strength
inspired from the stable diffusion img2img pipeline, init latents are initialised by converting the init image into a VAE latent and adding noise (based upon the strength parameter passed in), e.g. random when strength = 1, or the init image at strength = 0.
* WIP: Added a unit test for the new strength parameter in the StableDiffusionInpaintingPipeline
still need to add correct regression values
* Created a is_strength_max to initialise from pure random noise
* Updated unit tests w.r.t new strength parameter + fixed new strength unit test
* renamed parameter to avoid confusion with variable of same name
* Updated regression values for new strength test - now passes
* removed 'copied from' comment as this method is now different and divergent from the cpy
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_inpaint.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Ensure backwards compatibility for prepare_mask_and_masked_image
created a return_image boolean and initialised to false
* Ensure backwards compatibility for prepare_latents
* Fixed copy check typo
* Fixes w.r.t backward compibility changes
* make style
* keep function argument ordering same for backwards compatibility in callees with copied from statements
* make fix-copies
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: William Berman <WLBberman@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
* enable deterministic pytorch and cuda operations.
* disable manual seeding.
* make style && make quality for unet_2d tests.
* enable determinism for the unet2dconditional model.
* add CUBLAS_WORKSPACE_CONFIG for better reproducibility.
* relax tolerance (very weird issue, though).
* revert to torch manual_seed() where needed.
* relax more tolerance.
* better placement of the cuda variable and relax more tolerance.
* enable determinism for 3d condition model.
* relax tolerance.
* add: determinism to alt_diffusion.
* relax tolerance for alt diffusion.
* dance diffusion.
* dance diffusion is flaky.
* test_dict_tuple_outputs_equivalent edit.
* fix two more tests.
* fix more ddim tests.
* fix: argument.
* change to diff in place of difference.
* fix: test_save_load call.
* test_save_load_float16 call.
* fix: expected_max_diff
* fix: paint by example.
* relax tolerance.
* add determinism to 1d unet model.
* torch 2.0 regressions seem to be brutal
* determinism to vae.
* add reason to skipping.
* up tolerance.
* determinism to vq.
* determinism to cuda.
* determinism to the generic test pipeline file.
* refactor general pipelines testing a bit.
* determinism to alt diffusion i2i
* up tolerance for alt diff i2i and audio diff
* up tolerance.
* determinism to audioldm
* increase tolerance for audioldm lms.
* increase tolerance for paint by paint.
* increase tolerance for repaint.
* determinism to cycle diffusion and sd 1.
* relax tol for cycle diffusion 🚲
* relax tol for sd 1.0
* relax tol for controlnet.
* determinism to img var.
* relax tol for img variation.
* tolerance to i2i sd
* make style
* determinism to inpaint.
* relax tolerance for inpaiting.
* determinism for inpainting legacy
* relax tolerance.
* determinism to instruct pix2pix
* determinism to model editing.
* model editing tolerance.
* panorama determinism
* determinism to pix2pix zero.
* determinism to sag.
* sd 2. determinism
* sd. tolerance
* disallow tf32 matmul.
* relax tolerance is all you need.
* make style and determinism to sd 2 depth
* relax tolerance for depth.
* tolerance to diffedit.
* tolerance to sd 2 inpaint.
* up tolerance.
* determinism in upscaling.
* tolerance in upscaler.
* more tolerance relaxation.
* determinism to v pred.
* up tol for v_pred
* unclip determinism
* determinism to unclip img2img
* determinism to text to video.
* determinism to last set of tests
* up tol.
* vq cumsum doesn't have a deterministic kernel
* relax tol
* relax tol
* add inferring_controlnet_cond_batch
* Revert "add inferring_controlnet_cond_batch"
This reverts commit abe8d6311d.
* set guess_mode to True
whenever global_pool_conditions is True
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* nit
* add integration test
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* StableDiffusionInpaintingPipeline now resizes input images and masks w.r.t to passed input height and width. Default is already set to 512. This addresses the common tensor mismatch error. Also moved type check into relevant funciton to keep main pipeline body tidy.
* Fixed StableDiffusionInpaintingPrepareMaskAndMaskedImageTests
Due to previous commit these tests were failing as height and width need to be passed into the prepare_mask_and_masked_image function, I have updated the code and added a height/width variable per unit test as it seemed more appropriate than the current hard coded solution
* Added a resolution test to StableDiffusionInpaintPipelineSlowTests
this unit test simply gets the input and resizes it into some that would fail (e.g. would throw a tensor mismatch error/not a mult of 8). Then passes it through the pipeline and verifies it produces output with correct dims w.r.t the passed height and width
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Fix more torch compile breaks
* add tests
* Fix all
* fix controlnet
* fix more
* Add Horace He as co-author.
>
>
Co-authored-by: Horace He <horacehe2007@yahoo.com>
* Add Horace He as co-author.
Co-authored-by: Horace He <horacehe2007@yahoo.com>
---------
Co-authored-by: Horace He <horacehe2007@yahoo.com>
* fix more
* Fix more
* fix more
* Apply suggestions from code review
* fix
* make style
* make fix-copies
* fix
* make sure torch compile
* Clean
* fix test
* Update Pix2PixZero Auto-correlation Loss
* Add fast inversion tests
* Clarify purpose and mark as deprecated
Fix inversion prompt broadcasting
* Register modules set to `None` in config for `test_save_load_optional_components`
* Update new tests to coordinate with #2953
* 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
* fix: norm group test for UNet3D.
* chore: speed up the panorama tests (fast).
* set default value of _test_inference_batch_single_identical.
* fix: batch_sizes default value.
* add support for prompt embeds to SD ONNX pipeline
* fix up the pipeline copies
* add prompt embeds param to other ONNX pipelines
* fix up prompt embeds param for SD upscaling ONNX pipeline
* add missing type annotations to ONNX pipes
* ⚙️chore(train_controlnet) fix typo in logger message
* ⚙️chore(models) refactor modules order; make them the same as calling order
When printing the BasicTransformerBlock to stdout, I think it's crucial that the attributes order are shown in proper order. And also previously the "3. Feed Forward" comment was not making sense. It should have been close to self.ff but it's instead next to self.norm3
* correct many tests
* remove bogus file
* make style
* correct more tests
* finish tests
* fix one more
* make style
* make unclip deterministic
* ⚙️chore(models/attention) reorganize comments in BasicTransformerBlock class
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* add load textual inversion embeddings draft
* fix quality
* fix typo
* make fix copies
* move to textual inversion mixin
* make it accept from sd-concept library
* accept list of paths to embeddings
* fix styling of stable diffusion pipeline
* add dummy TextualInversionMixin
* add docstring to textualinversionmixin
* add load textual inversion embeddings draft
* fix quality
* fix typo
* make fix copies
* move to textual inversion mixin
* make it accept from sd-concept library
* accept list of paths to embeddings
* fix styling of stable diffusion pipeline
* add dummy TextualInversionMixin
* add docstring to textualinversionmixin
* add case for parsing embedding from auto1111 UI format
Co-authored-by: Evan Jones <evan.a.jones3@gmail.com>
Co-authored-by: Ana Tamais <aninhamoraestamais@gmail.com>
* fix style after rebase
* move textual inversion mixin to loaders
* move mixin inheritance to DiffusionPipeline from StableDiffusionPipeline)
* update dummy class name
* addressed allo comments
* fix old dangling import
* fix style
* proposal
* remove bogus
* Apply suggestions from code review
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Will Berman <wlbberman@gmail.com>
* finish
* make style
* up
* fix code quality
* fix code quality - again
* fix code quality - 3
* fix alt diffusion code quality
* fix model editing pipeline
* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Finish
---------
Co-authored-by: Evan Jones <evan.a.jones3@gmail.com>
Co-authored-by: Ana Tamais <aninhamoraestamais@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Will Berman <wlbberman@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 76ea9c856f.
* 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>
