GitLab

lu lambdas

* why mdx?

* why mdx?

* why mdx?

* no x for kandinksy either

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

* start with stable diffusion

* fix

* finish stable diffusion pipelines

* fix path to pipeline output

* fix flax paths

* fix copies

* add up to score sde ve

* finish first pass of pipelines

* fix copies

* second review

* align doc titles

* more review fixes

* final review

* add entry for safe stable diffusion to the sd overview page.

* add missing pipelines o the broader overview section in the pipelines.

* address PR feedback./

* Update Pix2PixZero Auto-correlation Loss

* Add Stable Diffusion DiffEdit pipeline

* Add draft documentation and import code

* Bugfixes and refactoring

* Add option to not decode latents in the inversion process

* Harmonize preprocessing

* Revert "Update Pix2PixZero Auto-correlation Loss"

This reverts commit b218062fed08d6cc164206d6cb852b2b7b00847a.

* Update annotations

* rename `compute_mask` to `generate_mask`

* Update documentation

* Update docs

* Update Docs

* Fix copy

* Change shape of output latents to batch first

* Update docs

* Add first draft for tests

* Bugfix and update tests

* Add `cross_attention_kwargs` support for all pipeline methods

* Fix Copies

* Add support for PIL image latents

Add support for mask broadcasting

Update docs and tests

Align `mask` argument to `mask_image`

Remove height and width arguments

* Enable MPS Tests

* Move example docstrings

* Fix test

* Fix test

* fix pipeline inheritance

* Harmonize `prepare_image_latents` with StableDiffusionPix2PixZeroPipeline

* Register modules set to `None` in config for `test_save_load_optional_components`

* Move fixed logic to specific test class

* Clean changes to other pipelines

* Update new tests to coordinate with #2953

* Update slow tests for better results

* Safety to avoid potential problems with torch.inference_mode

* Add reference in SD Pipeline Overview

* Fix tests again

* Enforce determinism in noise for generate_mask

* Fix copies

* Widen test tolerance for fp16 based on `test_stable_diffusion_upscale_pipeline_fp16`

* Add LoraLoaderMixin and update `prepare_image_latents`

* clean up repeat and reg

* bugfix

* Remove invalid args from docs

Suppress spurious warning by repeating image before latent to mask gen

* TIME first commit

* styling.

* styling 2.

* fixes; tests

* apply styling and doc fix.

* remove sups.

* fixes

* remove temp file

* move augmentations to const

* added doc entry

* code quality

* customize augmentations

* quality

* quality

---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* 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.

* 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>

* being pix2pix

* ifx

* cfg image_latents

* fix some docstr

* fix

* fix

* hack

* fix

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

* add comments to explain the hack

* move __call__ to the top

* doc

* remove height and width

* remove depreications

* fix doc str

* quality

* fast tests

* chnage model id

* fast tests

* fix test

* address Pedro's comments

* copyright

* Simple doc page.

* Apply suggestions from code review

* style

* Remove import

* address some review comments

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

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

* init for korean docs

* edit build yml file for multi language docs

* edit one more build yml file for multi language docs

* add title for get_frontmatter error

only have api docstring once for sD

* add a doc page for each pipeline under api/pipelines/stable_diffusion
* add pipeline examples to docstrings
* updated stable_diffusion_2 page
* updated default markdown syntax to list methods based on https://github.com/huggingface/diffusers/pull/1870


* add function decorator
Co-authored-by: yiyixuxu <yixu@Yis-MacBook-Pro.lan>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* [Docs] Improve docs

* up

* begin depth pipeline

* add depth estimation model

* fix prepare_depth_mask

* add a comment about autocast

* copied from, quality, cleanup

* begin tests

* handle tensors

* norm image tensor

* fix batch size

* fix tests

* fix enable_sequential_cpu_offload

* fix save load

* fix test_save_load_float16

* fix test_save_load_optional_components

* fix test_float16_inference

* fix test_cpu_offload_forward_pass

* fix test_dict_tuple_outputs_equivalent

* up

* fix fast tests

* fix test_stable_diffusion_img2img_multiple_init_images

* fix few more fast tests

* don't use device map for DPT

* fix test_stable_diffusion_pipeline_with_sequential_cpu_offloading

* accept external depth maps

* prepare_depth_mask -> prepare_depth_map

* fix file name

* fix file name

* quality

* check transformers version

* fix test names

* use skipif

* fix import

* add docs

* skip tests on mps

* correct version

* uP

* Update docs/source/api/pipelines/stable_diffusion_2.mdx

* fix fix-copies

* fix fix-copies
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: anton- <anton@huggingface.co>

* 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

* 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>

* 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>

* make fix copies again

* Fix typo

* 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>

* add euler scheduler in docs

* add a section for how to use different scheds

* address patrck's comments

* add community pipeline docs

* fix style in code snippets (lol)

* clean up loading docs

* add license to doc files

* fix some weird links

* [Stable Diffusion] Add components function

* uP

fix table formatting (add blank line)

* [Outputs] Improve syntax

* improve more

* fix docstring return

* correct all

* uP
Co-authored-by: Mishig Davaadorj <dmishig@gmail.com>

* Start

* up

* up

* finish

* Initial description of Stable Diffusion pipeline.

* Placeholder docstrings to test preview.

* Add docstrings to Stable Diffusion pipeline.

* Style

* Docs for all the SD pipelines + attention slicing.

* Style: wrap long lines.

* first pass at docs structure

* minor reformatting, add github actions for docs

* populate docs (primarily from README, some writing)