GitLab

* up

* up

* finish

* finish

* up

* up

* finish

* feat: switch core pipelines to use image arg

* test: update tests for core pipelines

* feat: switch examples to use image arg

* docs: update docs to use image arg

* style: format code using black and doc-builder

* fix: deprecate use of init_image in all pipelines

* Add doc for Stable Diffusion on Habana Gaudi

* Make style

* Add benchmark

* Center-align columns in the benchmark table

* Add better docs xformers

* update

* Apply suggestions from code review

* fix

* StableDiffusion: Decode latents separately to run larger batches

* Move VAE sliced decode under enable_vae_sliced_decode and vae.enable_sliced_decode

* Rename sliced_decode to slicing

* fix whitespace

* fix quality check and repository consistency

* VAE slicing tests and documentation

* API doc hooks for VAE slicing

* reformat vae slicing tests

* Skip VAE slicing for one-image batches

* Documentation tweaks for VAE slicing
Co-authored-by: Ilmari Heikkinen <ilmari@fhtr.org>

fixed typos

* up

* up

* up

* up

* StableDiffusionUpscalePipeline

* fix a few things

* make it better

* fix image batching

* run vae in fp32

* fix docstr

* resize to mul of 64

* doc

* remove safety_checker

* add max_noise_level

* fix Copied

* begin tests

* slow tests

* default max_noise_level

* remove kwargs

* doc

* fix

* fix fast tests

* fix fast tests

* no sf

* don't offload vae
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* up

* convert dual unet

* revert dual attn

* adapt for vd-official

* test the full pipeline

* mixed inference

* mixed inference for text2img

* add image prompting

* fix clip norm

* split text2img and img2img

* fix format

* refactor text2img

* mega pipeline

* add optimus

* refactor image var

* wip text_unet

* text unet end to end

* update tests

* reshape

* fix image to text

* add some first docs

* dual guided pipeline

* fix token ratio

* propose change

* dual transformer as a native module

* DualTransformer(nn.Module)

* DualTransformer(nn.Module)

* correct unconditional image

* save-load with mega pipeline

* remove image to text

* up

* uP

* fix

* up

* final fix

* remove_unused_weights

* test updates

* save progress

* uP

* fix dual prompts

* some fixes

* finish

* style

* finish renaming

* up

* fix

* fix

* fix

* finish
Co-authored-by: anton-l <anton@huggingface.co>

* add StableDiffusionImageVariationPipeline

* add ini init

* use CLIPVisionModelWithProjection

* fix _encode_image

* add copied from

* fix copies

* add doc

* handle tensor in _encode_image

* add tests

* correct model_id

* remove copied from in enable_sequential_cpu_offload

* fix tests

* make slow tests pass

* update slow tests

* use temp model for now

* fix test_stable_diffusion_img_variation_intermediate_state

* fix test_stable_diffusion_img_variation_intermediate_state

* check for torch.Tensor

* quality

* fix name

* fix slow tests

* install transformers from source

* fix install

* fix install

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

* input_image -> image

* remove deprication warnings

* fix test_stable_diffusion_img_variation_multiple_images

* make flake happy
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Add pipeline_stable_diffusion_safe.py to pipelines

* Fix repository consistency

Ran make fix-copies after adding new pipline

* Add Paper/Equation reference for parameters to doc string

* Ensure code style and quality

* Perform code refactoring

* Fix copies inherited from merge with huggingface/main

* Add docs

* Fix code style

* Fix errors in documentation

* Fix refactoring error

* remove debugging print statement

* added Safe Latent Diffusion tests

* Fix style

* Fix style

* Add pre-defined safety configurations

* Fix line-break

* fix some tests

* finish

* Change safety checker

* Add missing safety_checker.py file

* Remove unused imports
Co-authored-by: PatrickSchrML <patrick_schramowski@hotmail.de>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update alt_diffusion.mdx

* Update alt_diffusion.mdx

* add docs for multi-modal

* many changes

* fix docs build

* fix links

* Update docs/source/using-diffusers/other-modalities.mdx
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* make fix copies again

* Fix typo

* Better error message for transformers dummy

* [PIL] Better deprecation functionality

* up

* add conversion script for vae

* up

* up

* some fixes

* add text model

* use the correct config

* add docs

* move model in it's own file

* move model in its own file

* pass attenion mask to text encoder

* pass attn mask to uncond inputs

* quality

* fix image2image

* add imag2image in init

* fix import

* fix one more import

* fix import, dummy objetcs

* fix copied from

* up

* finish
Co-authored-by: patil-suraj <surajp815@gmail.com>

* add conversion script for vae

* uP

* uP

* more changes

* push

* up

* finish again

* up

* up

* up

* up

* finish

* up

* uP

* up

* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Anton Lozhkov <anton@huggingface.co>
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* up

* up
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Anton Lozhkov <anton@huggingface.co>
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* re-add RL model code

* match model forward api

* add register_to_config, pass training tests

* fix tests, update forward outputs

* remove unused code, some comments

* add to docs

* remove extra embedding code

* unify time embedding

* remove conv1d output sequential

* remove sequential from conv1dblock

* style and deleting duplicated code

* clean files

* remove unused variables

* clean variables

* add 1d resnet block structure for downsample

* rename as unet1d

* fix renaming

* rename files

* add get_block(...) api

* unify args for model1d like model2d

* minor cleaning

* fix docs

* improve 1d resnet blocks

* fix tests, remove permuts

* fix style

* add output activation

* rename flax blocks file

* Add Value Function and corresponding example script to Diffuser implementation (#884)

* valuefunction code

* start example scripts

* missing imports

* bug fixes and placeholder example script

* add value function scheduler

* load value function from hub and get best actions in example

* very close to working example

* larger batch size for planning

* more tests

* merge unet1d changes

* wandb for debugging, use newer models

* success!

* turns out we just need more diffusion steps

* run on modal

* merge and code cleanup

* use same api for rl model

* fix variance type

* wrong normalization function

* add tests

* style

* style and quality

* edits based on comments

* style and quality

* remove unused var

* hack unet1d into a value function

* add pipeline

* fix arg order

* add pipeline to core library

* community pipeline

* fix couple shape bugs

* style

* Apply suggestions from code review
Co-authored-by: Nathan Lambert <nathan@huggingface.co>

* update post merge of scripts

* add mdiblock / outblock architecture

* Pipeline cleanup (#947)

* valuefunction code

* start example scripts

* missing imports

* bug fixes and placeholder example script

* add value function scheduler

* load value function from hub and get best actions in example

* very close to working example

* larger batch size for planning

* more tests

* merge unet1d changes

* wandb for debugging, use newer models

* success!

* turns out we just need more diffusion steps

* run on modal

* merge and code cleanup

* use same api for rl model

* fix variance type

* wrong normalization function

* add tests

* style

* style and quality

* edits based on comments

* style and quality

* remove unused var

* hack unet1d into a value function

* add pipeline

* fix arg order

* add pipeline to core library

* community pipeline

* fix couple shape bugs

* style

* Apply suggestions from code review

* clean up comments

* convert older script to using pipeline and add readme

* rename scripts

* style, update tests

* delete unet rl model file

* remove imports in src
Co-authored-by: Nathan Lambert <nathan@huggingface.co>

* Update src/diffusers/models/unet_1d_blocks.py

* Update tests/test_models_unet.py

* RL Cleanup v2 (#965)

* valuefunction code

* start example scripts

* missing imports

* bug fixes and placeholder example script

* add value function scheduler

* load value function from hub and get best actions in example

* very close to working example

* larger batch size for planning

* more tests

* merge unet1d changes

* wandb for debugging, use newer models

* success!

* turns out we just need more diffusion steps

* run on modal

* merge and code cleanup

* use same api for rl model

* fix variance type

* wrong normalization function

* add tests

* style

* style and quality

* edits based on comments

* style and quality

* remove unused var

* hack unet1d into a value function

* add pipeline

* fix arg order

* add pipeline to core library

* community pipeline

* fix couple shape bugs

* style

* Apply suggestions from code review

* clean up comments

* convert older script to using pipeline and add readme

* rename scripts

* style, update tests

* delete unet rl model file

* remove imports in src

* add specific vf block and update tests

* style

* Update tests/test_models_unet.py
Co-authored-by: Nathan Lambert <nathan@huggingface.co>

* fix quality in tests

* fix quality style, split test file

* fix checks / tests

* make timesteps closer to main

* unify block API

* unify forward api

* delete lines in examples

* style

* examples style

* all tests pass

* make style

* make dance_diff test pass

* Refactoring RL PR (#1200)

* init file changes

* add import utils

* finish cleaning files, imports

* remove import flags

* clean examples

* fix imports, tests for merge

* update readmes

* hotfix for tests

* quality

* fix some tests

* change defaults

* more mps test fixes

* unet1d defaults

* do not default import experimental

* defaults for tests

* fix tests

* fix-copies

* fix

* changes per Patrik's comments (#1285)

* changes per Patrik's comments

* update conversion script

* fix renaming

* skip more mps tests

* last test fix

* Update examples/rl/README.md
Co-authored-by: Ben Glickenhaus <benglickenhaus@gmail.com>

fix link typo

update img2img example

* Add a reference to the name 'Sampler'

- Facilitate people that are familiar with the name samplers to understand that we call that schedulers
- Better SEO if people are googling for samplers to find our library as well

* Update README.md with a reference to 'Sampler'

* Add ldm super resolution pipeline

* style

* fix copies

* style

* fix doc

* Update src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion_superresolution.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion_superresolution.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion_superresolution.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Update src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion_superresolution.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* add doc

* address comments

* address comments

* fix doc

* minor

* add tests

* add tests

* load text encoder from subfolder

* fix test

* fix test

* style

* style

* handle mps latents

* unfix typo

* unfix typo

* Update tests/pipelines/latent_diffusion/test_latent_diffusion_superresolution.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* fix set_timesteps mps

* fix set_timesteps mps

* Update src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion_superresolution.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Update src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion_superresolution.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Update src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion_superresolution.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Update src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion_superresolution.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* style

* test 64x64 instead of 256x256
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

Link to Dreambooth blog post instead of W&B report.

* add loading script

* Apply suggestions from code review

* Apply suggestions from code review
Co-authored-by: Anton Lozhkov <anton@huggingface.co>
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* correct

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

* uP
Co-authored-by: Anton Lozhkov <anton@huggingface.co>
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Change title to match the sidebar in _toctree.

* Fix custom pipe link, add link to contribute.

* Fix community pipeline links.

* add dpmsolver discrete pytorch scheduler

* fix some typos in dpm-solver pytorch

* add dpm-solver pytorch in stable-diffusion pipeline

* add jax/flax version dpm-solver

* change code style

* change code style

* add docs

* add `add_noise` method for dpmsolver

* add pytorch unit test for dpmsolver

* add dummy object for pytorch dpmsolver

* Update src/diffusers/schedulers/scheduling_dpmsolver_discrete.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Update tests/test_config.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Update tests/test_config.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* resolve the code comments

* rename the file

* change class name

* fix code style

* add auto docs for dpmsolver multistep

* add more explanations for the stabilizing trick (for steps < 15)

* delete the dummy file

* change the API name of predict_epsilon, algorithm_type and solver_type

* add compatible lists
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Add CycleDiffusion pipeline for Stable Diffusion

* Add the option of passing noise to DDIMScheduler

Add the option of providing the noise itself to DDIMScheduler, instead of the random seed generator.

* Update README.md

* Update README.md

* Update pipeline_stable_diffusion_cycle_diffusion.py

* Update pipeline_stable_diffusion_cycle_diffusion.py

* Update pipeline_stable_diffusion_cycle_diffusion.py

* Update pipeline_stable_diffusion_cycle_diffusion.py

* Update scheduling_ddim.py

* Update import format

* Update pipeline_stable_diffusion_cycle_diffusion.py

* Update scheduling_ddim.py

* Update src/diffusers/schedulers/scheduling_ddim.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/schedulers/scheduling_ddim.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/schedulers/scheduling_ddim.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/schedulers/scheduling_ddim.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/schedulers/scheduling_ddim.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update scheduling_ddim.py

* Update scheduling_ddim.py

* Update scheduling_ddim.py

* add two tests

* Update pipeline_stable_diffusion_cycle_diffusion.py

* Update pipeline_stable_diffusion_cycle_diffusion.py

* Update README.md

* Rename pipeline name as suggested in the latest reviewer comment

* Update test_pipelines.py

* Update test_pipelines.py

* Update test_pipelines.py

* Update pipeline_stable_diffusion_cycle_diffusion.py

* Remove the generator

This generator does not control all randomness during sampling, which can be misleading.

* Update optimal hyperparameters

* Update src/diffusers/pipelines/stable_diffusion/README.md
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Update src/diffusers/pipelines/stable_diffusion/README.md
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Update src/diffusers/pipelines/stable_diffusion/README.md
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Apply suggestions from code review

* uP

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_cycle_diffusion.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* up

* up

* Replace assert with ValueError

* finish docs
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>

Do not require PyTorch nightlies.

* make accelerate hard dep

* default fast init

* move params to cpu when device map is None

* handle device_map=None

* handle torch < 1.9

* remove device_map="auto"

* style

* add accelerate in torch extra

* remove accelerate from extras["test"]

* raise an error if torch is available but not accelerate

* update installation docs

* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* improve defautl loading speed even further, allow disabling fats loading

* address review comments

* adapt the tests

* fix test_stable_diffusion_fast_load

* fix test_read_init

* temp fix for dummy checks

* Trigger Build

* Apply suggestions from code review
Co-authored-by: Anton Lozhkov <anton@huggingface.co>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Anton Lozhkov <anton@huggingface.co>

* Changes for VQ-diffusion VQVAE

Add specify dimension of embeddings to VQModel:
`VQModel` will by default set the dimension of embeddings to the number
of latent channels. The VQ-diffusion VQVAE has a smaller
embedding dimension, 128, than number of latent channels, 256.

Add AttnDownEncoderBlock2D and AttnUpDecoderBlock2D to the up and down
unet block helpers. VQ-diffusion's VQVAE uses those two block types.

* Changes for VQ-diffusion transformer

Modify attention.py so SpatialTransformer can be used for
VQ-diffusion's transformer.

SpatialTransformer:
- Can now operate over discrete inputs (classes of vector embeddings) as well as continuous.
- `in_channels` was made optional in the constructor so two locations where it was passed as a positional arg were moved to kwargs
- modified forward pass to take optional timestep embeddings

ImagePositionalEmbeddings:
- added to provide positional embeddings to discrete inputs for latent pixels

BasicTransformerBlock:
- norm layers were made configurable so that the VQ-diffusion could use AdaLayerNorm with timestep embeddings
- modified forward pass to take optional timestep embeddings

CrossAttention:
- now may optionally take a bias parameter for its query, key, and value linear layers

FeedForward:
- Internal layers are now configurable

ApproximateGELU:
- Activation function in VQ-diffusion's feedforward layer

AdaLayerNorm:
- Norm layer modified to incorporate timestep embeddings

* Add VQ-diffusion scheduler

* Add VQ-diffusion pipeline

* Add VQ-diffusion convert script to diffusers

* Add VQ-diffusion dummy objects

* Add VQ-diffusion markdown docs

* Add VQ-diffusion tests

* some renaming

* some fixes

* more renaming

* correct

* fix typo

* correct weights

* finalize

* fix tests

* Apply suggestions from code review
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

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

* finish

* finish

* up
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* feat: add repaint

* fix: fix quality check with `make fix-copies`

* fix: remove old unnecessary arg

* chore: change default to DDPM (looks better in experiments)

* ".to(device)" changed to "device="
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

* make generator device-specific
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

* make generator device-specific and change shape
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

* fix: add preprocessing for image and mask
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

* fix: update test
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

* Update src/diffusers/pipelines/repaint/pipeline_repaint.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Add docs and examples

* Fix toctree
Co-authored-by: fja <fja@zurich.ibm.com>
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Anton Lozhkov <anton@huggingface.co>

* Rename latent

* uP

* add euler scheduler in docs

* add a section for how to use different scheds

* address patrck's comments

* 2x speedup using memory efficient attention

* remove einops dependency

* Swap K, M in op instantiation

* Simplify code, remove unnecessary maybe_init call and function, remove unused self.scale parameter

* make xformers a soft dependency

* remove one-liner functions

* change one letter variable to appropriate names

* Remove Env variable dependency, remove MemoryEfficientCrossAttention class and use enable_xformers_memory_efficient_attention method

* Add memory efficient attention toggle to img2img and inpaint pipelines

* Clearer management of xformers' availability

* update optimizations markdown to add info about memory efficient attention

* add benchmarks for TITAN RTX

* More detailed explanation of how the mem eff benchmark were ran

* Removing autocast from optimization markdown

* import_utils: import torch only if is available
Co-authored-by: Nouamane Tazi <nouamane98@gmail.com>

* [Better scheduler docs] Improve usage examples of schedulers

* finish

* fix warnings and add test

* finish

* more replacements

* adapt fast tests hf token

* correct more

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

* Integrate compatibility with euler
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>