* 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>
* added dit model
* import
* initial pipeline
* initial convert script
* initial pipeline
* make style
* raise valueerror
* single function
* rename classes
* use DDIMScheduler
* timesteps embedder
* samples to cpu
* fix var names
* fix numpy type
* use timesteps class for proj
* fix typo
* fix arg name
* flip_sin_to_cos and better var names
* fix C shape cal
* make style
* remove unused imports
* cleanup
* add back patch_size
* initial dit doc
* typo
* Update docs/source/api/pipelines/dit.mdx
Co-authored-by: Suraj Patil <surajp815@gmail.com>
* added copyright license headers
* added example usage and toc
* fix variable names asserts
* remove comment
* added docs
* fix typo
* upstream changes
* set proper device for drop_ids
* added initial dit pipeline test
* update docs
* fix imports
* make fix-copies
* isort
* fix imports
* get rid of more magic numbers
* fix code when guidance is off
* remove block_kwargs
* cleanup script
* removed to_2tuple
* use FeedForward class instead of another MLP
* style
* work on mergint DiTBlock with BasicTransformerBlock
* added missing final_dropout and args to BasicTransformerBlock
* use norm from block
* fix arg
* remove unused arg
* fix call to class_embedder
* use timesteps
* make style
* attn_output gets multiplied
* removed commented code
* use Transformer2D
* use self.is_input_patches
* fix flags
* fixed conversion to use Transformer2DModel
* fixes for pipeline
* remove dit.py
* fix timesteps device
* use randn_tensor and fix fp16 inf.
* timesteps_emb already the right dtype
* fix dit test class
* fix test and style
* fix norm2 usage in vq-diffusion
* added author names to pipeline and lmagenet labels link
* fix tests
* use norm_type as string
* rename dit to transformer
* fix name
* fix test
* set norm_type = "layer" by default
* fix tests
* do not skip common tests
* Update src/diffusers/models/attention.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>
* revert AdaLayerNorm API
* fix norm_type name
* make sure all components are in eval mode
* revert norm2 API
* compact
* finish deprecation
* add slow tests
* remove @
* refactor some stuff
* upload
* Update src/diffusers/pipelines/dit/pipeline_dit.py
* finish more
* finish docs
* improve docs
* finish docs
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: William Berman <WLBberman@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
re: https://github.com/huggingface/diffusers/issues/1857
We relax some of the checks to deal with unclip reproducibility issues. Mainly by checking the average pixel difference (measured w/in 0-255) instead of the max pixel difference (measured w/in 0-1).
- [x] add mixin to UnCLIPPipelineFastTests
- [x] add mixin to UnCLIPImageVariationPipelineFastTests
- [x] Move UnCLIPPipeline flags in mixin to base class
- [x] Small MPS fixes for F.pad and F.interpolate
- [x] Made test unCLIP model's dimensions smaller to run tests faster
* [Batched Generators] all batched generators
* up
* up
* up
* up
* up
* up
* up
* up
* up
* up
* up
* up
* up
* up
* up
* up
* hey
* up again
* fix tests
* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* correct tests
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* [SD] Make sure batched input works correctly
* uP
* uP
* up
* up
* uP
* up
* fix mask stuff
* up
* uP
* more up
* up
* uP
* up
* finish
* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* 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>
YiYi Xu