GitLab

* Batched load of textual inversions

- Only call resize_token_embeddings once per batch as it is the most expensive operation
- Allow pretrained_model_name_or_path and token to be an optional list
- Remove Dict from type annotation pretrained_model_name_or_path as it was not supported in this function
- Add comment that single files (e.g. .pt/.safetensors) are supported
- Add comment for token parameter
- Convert token override log message from warning to info

* Update src/diffusers/loaders.py

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

* Update condition for None tokens

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

* add karras sigma to lms discrete scheduler

* add test for lms_scheduler karras

* reformat test lms

* test: Added test case

* fix: fixed type checking issue on _encode_prompt

* fix: fixed copies consistency

* fix: one copy was not sufficient

The argument `upsample_size` needs to be added to these modules to allow compatibility with other blocks that require this argument.

* add SDE variant of DPM-Solver and DPM-Solver++

* add test

* fix typo

* fix typo

* fix multistep dpmsolver for cosine schedule (deepfloy-if)

* fix a typo

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

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

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

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

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

* update all dpmsolver (singlestep, multistep, dpm, dpm++) for cosine noise schedule

* add test, fix style

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

Fix missing variable assign

lol

* 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>

* refactor img2img VaeImageProcessor.postprocess

* remove copy from for init, run_safety_checker, decode_latents
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

---------
Co-authored-by: yiyixuxu <yixu@yis-macbook-pro.lan>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.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

A pipeline object stores the results in `images` not in `sample`.
Current code blocks don't work.

The note-seq package throws an error on import because the default installed version of Ipython
is not compatible with python 3.8 which we run in the CI.
https://github.com/huggingface/diffusers/actions/runs/4830121056/jobs/8605954838#step:7:9

* Allow disabling torch 2_0 attention

* make style

* Update src/diffusers/models/attention.py

* add constant lr with rules

* add constant with rules in TYPE_TO_SCHEDULER_FUNCTION

* add constant lr rate with rule

* hotfix code quality

* fix doc style

* change name constant_with_rules to piecewise constant

* 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

* 👽

 qol improvements for LoRA.

* better function name?

* fix: LoRA weight loading with the new format.

* address Patrick's comments.

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

* change wording around encouraging the use of load_lora_weights().

* fix: function name.

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

* config fixes

* deprecate get_input_dims

Co-authored-by: multimodalart <joaopaulo.passos+multimodal@gmail.com>

* removed unnecessary parameters from get_up_block and get_down_block functions

* adding resnet_skip_time_act, resnet_out_scale_factor and cross_attention_norm to get_up_block and get_down_block functions

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

* [2064]: Add stochastic sampler

* [2064]: Add stochastic sampler

* [2064]: Add stochastic sampler

* [2064]: Add stochastic sampler

* [2064]: Add stochastic sampler

* [2064]: Add stochastic sampler

* [2064]: Add stochastic sampler

* Review comments

* [Review comment]: Add is_torchsde_available()

* [Review comment]: Test and docs

* [Review comment]

* [Review comment]

* [Review comment]

* [Review comment]

* [Review comment]

---------
Co-authored-by: njindal <njindal@adobe.com>

* Post release

* fix more

* Add all files

* update

* Make sure vae is memory efficient for PT 1

* make style

* Add all files

* update

* add

* clean

* up

* clean up more

* fix more tests

* Improve docs further

* improve

* more fixes docs

* Improve docs more

* Update src/diffusers/models/unet_2d_condition.py

* fix

* up

* update doc links

* make fix-copies

* add safety checker and watermarker to stage 3 doc page code snippets

* speed optimizations docs

* memory optimization docs

* make style

* add watermarking snippets to doc string examples

* make style

* use pt_to_pil helper functions in doc strings

* skip mps tests

* Improve safety

* make style

* new logic

* fix

* fix bad onnx design

* make new stable diffusion upscale pipeline model arguments optional

* define has_nsfw_concept when non-pil output type

* lowercase linked to notebook name

---------
Co-authored-by: William Berman <WLBberman@gmail.com>

* Fix docs text inversion

* Apply suggestions from code review

sync cache version check from transformers

When the token used for textual inversion does not have any special symbols (e.g. it is not surrounded by <>), the tokenizer does not properly split the replacement tokens.  Adding a space for the padding tokens fixes this.

adding enable_vae_tiling and disable_val_tiling functions

* Make sure attention works with Torch 2_0

* make style

* Fix more

* Add karras pattern to discrete heun scheduler

* Add integration test

* Fix failing CI on pytorch test on M1 (mps)

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

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

* Add model offload to x4 upscaler

* fix

* 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