GitLab

* Replace `AttentionBlock` with `Attention`

* use _from_deprecated_attn_block check re: @patrickvonplaten

* 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

* Make sure attention works with Torch 2_0

* make style

* Fix more

* diffusers==0.14.0 update

* custom diffusion update

* custom diffusion update

* custom diffusion update

* custom diffusion update

* custom diffusion update

* custom diffusion update

* custom diffusion

* custom diffusion

* custom diffusion

* custom diffusion

* custom diffusion

* apply formatting and get rid of bare except.

* refactor readme and other minor changes.

* misc refactor.

* fix: repo_id issue and loaders logging bug.

* fix: save_model_card.

* fix: save_model_card.

* fix: save_model_card.

* add: doc entry.

* refactor doc,.

* custom diffusion

* custom diffusion

* custom diffusion

* apply style.

* remove tralining whitespace.

* fix: toctree entry.

* remove unnecessary print.

* custom diffusion

* custom diffusion

* custom diffusion test

* custom diffusion xformer update

* custom diffusion xformer update

* custom diffusion xformer update

---------
Co-authored-by: Nupur Kumari <nupurkumari@Nupurs-MacBook-Pro.local>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Nupur Kumari <nupurkumari@nupurs-mbp.wifi.local.cmu.edu>

* Better deprecation message

* Better deprecation message

* Better doc string

* Fixes

* fix more

* fix more

* Improve __getattr__

* correct more

* fix more

* fix

* Improve more

* more improvements

* fix more

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

* make style

* Fix all rest & add tests & remove old deprecation fns

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

* [Tests] parallelize

* finish folder structuring

* Parallelize tests more

* Correct saving of pipelines

* make sure logging level is correct

* try again

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

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

* inital commit for lora test cases

* help a bit with lora for 3d

* fixed lora tests

* replaced redundant code

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

* add only cross attention to simple attention blocks

* add test for only_cross_attention re: @patrickvonplaten

* mid_block_only_cross_attention better default

allow mid_block_only_cross_attention to default to
`only_cross_attention` when `only_cross_attention` is given
as a single boolean

* [Config] Fix config prints and save, load

* Only use potential nn.Modules for dtype and device

* Correct vae image processor

* make sure in_channels is not accessed directly

* make sure in channels is only accessed via config

* Make sure schedulers only access config attributes

* Make sure to access config in SAG

* Fix vae processor and make style

* add tests

* uP

* make style

* Fix more naming issues

* Final fix with vae config

* change more

speed up test

* Helper function to disable custom attention processors.

* Restore code deleted by mistake.

* Format

* Fix modeling_text_unet copy.

* Add AudioLDM

* up

* add vocoder

* start unet

* unconditional unet

* clap, vocoder and vae

* clean-up: conversion scripts

* fix: conversion script token_type_ids

* clean-up: pipeline docstring

* tests: from SD

* clean-up: cpu offload vocoder instead of safety checker

* feat: adapt tests to audioldm

* feat: add docs

* clean-up: amend pipeline docstrings

* clean-up: make style

* clean-up: make fix-copies

* fix: add doc path to toctree

* clean-up: args for conversion script

* clean-up: paths to checkpoints

* fix: use conditional unet

* clean-up: make style

* fix: type hints for UNet

* clean-up: docstring for UNet

* clean-up: make style

* clean-up: remove duplicate in docstring

* clean-up: make style

* clean-up: make fix-copies

* clean-up: move imports to start in code snippet

* fix: pass cross_attention_dim as a list/tuple to unet

* clean-up: make fix-copies

* fix: update checkpoint path

* fix: unet cross_attention_dim in tests

* film embeddings -> class embeddings

* Apply suggestions from code review
Co-authored-by: Will Berman <wlbberman@gmail.com>

* fix: unet film embed to use existing args

* fix: unet tests to use existing args

* fix: make style

* fix: transformers import and version in init

* clean-up: make style

* Revert "clean-up: make style"

This reverts commit 5d6d1f8b324f5583e7805dc01e2c86e493660d66.

* clean-up: make style

* clean-up: use pipeline tester mixin tests where poss

* clean-up: skip attn slicing test

* fix: add torch dtype to docs

* fix: remove conversion script out of src

* fix: remove .detach from 1d waveform

* fix: reduce default num inf steps

* fix: swap height/width -> audio_length_in_s

* clean-up: make style

* fix: remove nightly tests

* fix: imports in conversion script

* clean-up: slim-down to two slow tests

* clean-up: slim-down fast tests

* fix: batch consistent tests

* clean-up: make style

* clean-up: remove vae slicing fast test

* clean-up: propagate changes to doc

* fix: increase test tol to 1e-2

* clean-up: finish docs

* clean-up: make style

* feat: vocoder / VAE compatibility check

* feat: possibly expand / cut audio waveform

* fix: pipeline call signature test

* fix: slow tests output len

* clean-up: make style

* make style

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

* Skip mps in text-to-video tests.

* style

* Skip UNet3D mps tests.

* Remove warmup passes in mps tests.

* Update mps docs: no warmup pass in PyTorch 2

* Update imports.

* [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>

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

* [Tests] Correct PT2

* correct more

* move versatile to nightly

* up

* up

* again

* Apply suggestions from code review

* updated black format

* update black format

* make style format

* updated line endings

* update code formatting

* Update examples/research_projects/onnxruntime/text_to_image/train_text_to_image.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

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

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

* added vae gradient checkpointing test

* make style

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

* Adding `use_safetensors` argument to give more control to users

about which weights they use.

* Doc style.

* Rebased (not functional).

* Rebased and functional with tests.

* Style.

* Apply suggestions from code review

* Style.

* Addressing comments.

* Update tests/test_pipelines.py
Co-authored-by: Will Berman <wlbberman@gmail.com>

* Black ???

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

* rename file

* rename attention

* fix more

* rename more

* up

* more deprecation imports

* fixes

* fix AttnProcessor2_0

Fix use of AttnProcessor2_0 for cross attention with mask

* added scale_qk and out_bias flags

* fixed for xformers

* check if it has scale argument

* Update cross_attention.py

* check torch version

* fix sliced attn

* style

* set scale

* fix test

* fixed addedKV processor

* revert back AttnProcessor2_0

* if missing if

* fix inner_dim

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

* Fix regression introduced in #2448

* Style.

* Adding support for `safetensors` and LoRa.

* Adding metadata.

* 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.

* Fix running LoRA with xformers

* support disabling xformers

* reformat

* Add test

* before running make style

* remove left overs from flake8

* finish

* make fix-copies

* final fix

* more fixes

* Modify UNet2DConditionModel

- allow skipping mid_block

- adding a norm_group_size argument so that we can set the `num_groups` for group norm using `num_channels//norm_group_size`

- allow user to set dimension for the timestep embedding (`time_embed_dim`)

- the kernel_size for `conv_in` and `conv_out` is now configurable

- add random fourier feature layer (`GaussianFourierProjection`) for `time_proj`

- allow user to add the time and class embeddings before passing through the projection layer together - `time_embedding(t_emb + class_label))`

- added 2 arguments `attn1_types` and `attn2_types`

  * currently we have argument `only_cross_attention`: when it's set to `True`, we will have a to the
`BasicTransformerBlock` block with 2 cross-attention , otherwise we
get a self-attention followed by a cross-attention; in k-upscaler, we need to have blocks that include just one cross-attention, or self-attention -> cross-attention;
so I added `attn1_types` and `attn2_types` to the unet's argument list to allow user specify the attention types for the 2 positions in each block;  note that I stil kept
the `only_cross_attention` argument for unet for easy configuration, but it will be converted to `attn1_type` and `attn2_type` when passing down to the down blocks

- the position of downsample layer and upsample layer is now configurable

- in k-upscaler unet, there is only one skip connection per each up/down block (instead of each layer in stable diffusion unet), added `skip_freq = "block"` to support
this use case

- if user passes attention_mask to unet, it will prepare the mask and pass a flag to cross attention processer to skip the `prepare_attention_mask` step
inside cross attention block

add up/down blocks for k-upscaler

modify CrossAttention class

- make the `dropout` layer in `to_out` optional

- `use_conv_proj` - use conv instead of linear for all projection layers (i.e. `to_q`, `to_k`, `to_v`, `to_out`) whenever possible. note that when it's used to do cross
attention, to_k, to_v has to be linear because the `encoder_hidden_states` is not 2d

- `cross_attention_norm` - add an optional layernorm on encoder_hidden_states

- `attention_dropout`: add an optional dropout on attention score

adapt BasicTransformerBlock

- add an ada groupnorm layer  to conditioning attention input with timestep embedding

- allow skipping the FeedForward layer in between the attentions

- replaced the only_cross_attention argument with attn1_type and attn2_type for more flexible configuration

update timestep embedding: add new act_fn  gelu and an optional act_2

modified ResnetBlock2D

- refactored with AdaGroupNorm class (the timestep scale shift normalization)

- add `mid_channel` argument - allow the first conv to have a different output dimension from the second conv

- add option to use input AdaGroupNorm on the input instead of groupnorm

- add options to add a dropout layer after each conv

- allow user to set the bias in conv_shortcut (needed for k-upscaler)

- add gelu

adding conversion script for k-upscaler unet

add pipeline

* fix attention mask

* fix a typo

* fix a bug

* make sure model can be used with GPU

* make pipeline work with fp16

* fix an error in BasicTransfomerBlock

* make style

* fix typo

* some more fixes

* uP

* up

* correct more

* some clean-up

* clean time proj

* up

* uP

* more changes

* remove the upcast_attention=True from unet config

* remove attn1_types, attn2_types etc

* fix

* revert incorrect changes up/down samplers

* make style

* remove outdated files

* Apply suggestions from code review

* attention refactor

* refactor cross attention

* Apply suggestions from code review

* update

* up

* update

* Apply suggestions from code review

* finish

* Update src/diffusers/models/cross_attention.py

* more fixes

* up

* up

* up

* finish

* more corrections of conversion state

* act_2 -> act_2_fn

* remove dropout_after_conv from ResnetBlock2D

* make style

* simplify KAttentionBlock

* add fast test for latent upscaler pipeline

* add slow test

* slow test fp16

* make style

* add doc string for pipeline_stable_diffusion_latent_upscale

* add api doc page for latent upscaler pipeline

* deprecate attention mask

* clean up embeddings

* simplify resnet

* up

* clean up resnet

* up

* correct more

* up

* up

* improve a bit more

* correct more

* more clean-ups

* Update docs/source/en/api/pipelines/stable_diffusion/latent_upscale.mdx
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update docs/source/en/api/pipelines/stable_diffusion/latent_upscale.mdx
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* add docstrings for new unet config

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

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

* # Copied from

* encode the image if not latent

* remove force casting vae to fp32

* fix

* add comments about preconditioning parameters from k-diffusion paper

* attn1_type, attn2_type -> add_self_attention

* clean up get_down_block and get_up_block

* fix

* fixed a typo(?) in ada group norm

* update slice attention processer for cross attention

* update slice

* fix fast test

* update the checkpoint

* finish tests

* fix-copies

* fix-copy for modeling_text_unet.py

* make style

* make style

* fix f-string

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

* fix import

* correct changes

* fix resnet

* make fix-copies

* correct euler scheduler

* add missing #copied from for preprocess

* revert

* fix

* fix copies

* Update docs/source/en/api/pipelines/stable_diffusion/latent_upscale.mdx
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update docs/source/en/api/pipelines/stable_diffusion/latent_upscale.mdx
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update docs/source/en/api/pipelines/stable_diffusion/latent_upscale.mdx
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update docs/source/en/api/pipelines/stable_diffusion/latent_upscale.mdx
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update src/diffusers/models/cross_attention.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_latent_upscale.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_latent_upscale.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* clean up conversion script

* KDownsample2d,KUpsample2d -> KDownsample2D,KUpsample2D

* more

* Update src/diffusers/models/unet_2d_condition.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* remove prepare_extra_step_kwargs

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_latent_upscale.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

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

* fix a typo in timestep embedding

* remove num_image_per_prompt

* fix fasttest

* make style + fix-copies

* fix

* fix xformer test

* fix style

* doc string

* make style

* fix-copies

* docstring for time_embedding_norm

* make style

* final finishes

* make fix-copies

* fix tests

---------
Co-authored-by: yiyixuxu <yixu@yis-macbook-pro.lan>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* make tests deterministic

* run slow tests

* prepare for testing

* finish

* refactor

* add print statements

* finish more

* correct some test failures

* more fixes

* set up to correct tests

* more corrections

* up

* fix more

* more prints

* add

* up

* up

* up

* uP

* uP

* more fixes

* uP

* up

* up

* up

* up

* fix more

* up

* up

* clean tests

* up

* up

* up

* more fixes

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

* make

* correct

* finish

* finish
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* [Lora] first upload

* add first lora version

* upload

* more

* first training

* up

* correct

* improve

* finish loaders and inference

* up

* up

* fix more

* up

* finish more

* finish more

* up

* up

* change year

* revert year change

* Change lines

* Add cloneofsimo as co-author.
Co-authored-by: Simo Ryu <cloneofsimo@gmail.com>

* finish

* fix docs

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

* upload

* finish
Co-authored-by: Simo Ryu <cloneofsimo@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* move files a bit

* more refactors

* fix more

* more fixes

* fix more onnx

* make style

* upload

* fix

* up

* fix more

* up again

* up

* small fix

* Update src/diffusers/__init__.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

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

* first proposal

* rename

* up

* Apply suggestions from code review

* better

* up

* finish

* up

* rename

* correct versatile

* up

* up

* up

* up

* fix

* Apply suggestions from code review

* make style

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

* add error message
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* finish

* fix

* Update tests/models/test_models_unet_2d.py

* style
Co-authored-by: Anton Lozhkov <anton@huggingface.co>

* make attn slice recursive

* remove set_attention_slice from blocks

* fix copies

* make enable_attention_slicing base class method of DiffusionPipeline

* fix set_attention_slice

* fix set_attention_slice

* fix copies

* add tests

* up

* up

* up

* update

* up

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

* [CI] Add slow MPS tests

* fix yml

* temporarily resolve caching

* Tests: fix mps crashes.

* Skip test_load_pipeline_from_git on mps.

Not compatible with float16.

* Increase tolerance, use CPU generator, alt. slices.

* Move to nightly

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

* Add test

* up

* no bfloat16 for mps

* fix

* rename test