GitLab

* fix: how print training resume logs.

* propagate changes to text-to-image scripts.

* propagate changes to instructpix2pix.

* propagate changes to dreambooth

* propagate changes to custom diffusion and instructpix2pix

* propagate changes to kandinsky

* propagate changes to textual inv.

* debug

* fix: checkpointing.

* debug

* debug

* debug

* back to the square

* debug

* debug

* change condition order.

* debug

* debug

* debug

* debug

* revert to original

* clean

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

Update README_sdxl.md

* Update run_onnx_controlnet.py

* Update run_tensorrt_controlnet.py

add compute_snr() to training utils.

* merge with main

* fix flax example

* fix onnx example

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

* Timestep bias for fine-tuning SDXL

* Adjust parameter choices to include "range" and reword the help statements

* Condition our use of weighted timesteps on the value of timestep_bias_strategy

* style

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

SDXL microconditioning documentation should indicate the correct default order of parameters, so that developers know (#5155)

* SDXL microconditioning documentation should indicate the correct default order of parameters, so that developers know

* SDXL microconditioning documentation should indicate the correct default order of parameters, so that developers know

* empty

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

* Fix type annotation on Scheduler.from_pretrained

* Fix type annotation on PIL.Image

* min-SNR gamma for Dreambooth training

* Align the mse_loss_weights style with SDXL training example

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

Co-authored-by: bghira <bghira@users.github.com>

* Resolve v_prediction issue for min-SNR gamma weighted loss function

* Combine MSE loss calculation of epsilon and velocity, with a note about the application of the epsilon code to sample prediction

* style

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

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

Fixed `get_word_inds` mistake/typo in P2P community pipeline

The function `get_word_inds` was taking a string of text and either a word (str) or a word index (int) and returned the indices of token(s) the word would be encoded to.

However, there was a typo, in which in the second `if` branch the word was checked to be a `str` **again**, not `int`, which resulted in an [example code from the docs](https://github.com/huggingface/diffusers/tree/main/examples/community#prompt2prompt-pipeline) to result in an error

* Implement `CustomDiffusionAttnProcessor2_0`

* Doc-strings and type annotations for `CustomDiffusionAttnProcessor2_0`. (#1)

* Update attnprocessor.md

* Update attention_processor.py

* Interops for `CustomDiffusionAttnProcessor2_0`.

* Formatted `attention_processor.py`.

* Formatted doc-string in `attention_processor.py`

* Conditional CustomDiffusion2_0 for training example.

* Remove unnecessary reference impl in comments.

* Fix `save_attn_procs`.

* [LoRA] fix typo in attention_processor.py

fixes #5062

* make style

* make fix-copies, logger comented for torch compile

* convert tensorrt controlnet

* Fix code quality

* Fix code quality

* Fix code quality

* Fix code quality

* Fix code quality

* Fix code quality

* Fix number controlnet condition

* Add convert SD XL to onnx

* Add convert SD XL to tensorrt

* Add convert SD XL to tensorrt

* Add examples in comments

* Add examples in comments

* Add test onnx controlnet

* Add tensorrt test

* Remove copied

* Move file test to examples/community

* Remove script

* Remove script

* Remove text

* Fix import

---------
Co-authored-by: dotieuthien <thien.do@mservice.com.vn>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Add files via upload
Co-authored-by: Shahmatov Arseniy <62886550+cene555@users.noreply.github.com>
Co-authored-by: yiyixuxu <yixu310@gmail,com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* [Release 0.21] Bump version

* fix & remove

* fix more

* fix all, upload

* Initial commit P2P

* Replaced CrossAttention, added test skeleton

* bug fixes

* Updated docstring

* Removed unused function

* Created tests

* improved tests

- made fast inference tests faster
- corrected image shape assertions

* Corrected expected output shape in tests

* small fix: test inputs

* Update tests

- used conditional unet2d
- set expected image slices
- edit_kwargs are now not popped, so pipe can be run multiple times

* Fixed bug in int tests

* Fixed tests

* Linting

* Create prompt2prompt.md

* Added to docs toc

* Ran make fix-copies

* Fixed code blocks in docs

* Using same interface as StableDiffusionPipeline

* Fixed small test bug

* Added all options SDPipeline.__call_ has

* Fixed docstring; made __call__ like in SD

* Linting

* Added test for multiple prompts

* Improved docs

* Incorporated feedback

* Reverted formatting on unrelated files

* Moved prompt2prompt to community

- Moved prompt2prompt pipeline from main to community
- Deleted tests
- Moved documentation to community and shorted it

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

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

* examples fix t2i training

* make style

* initial commit

* move modules to import struct

* add dummy objects and _LazyModule

* add lazy import to schedulers

* clean up unused imports

* lazy import on models module

* lazy import for schedulers module

* add lazy import to pipelines module

* lazy import altdiffusion

* lazy import audio diffusion

* lazy import audioldm

* lazy import consistency model

* lazy import controlnet

* lazy import dance diffusion ddim ddpm

* lazy import deepfloyd

* lazy import kandinksy

* lazy imports

* lazy import semantic diffusion

* lazy imports

* lazy import stable diffusion

* move sd output to its own module

* clean up

* lazy import t2iadapter

* lazy import unclip

* lazy import versatile and vq diffsuion

* lazy import vq diffusion

* helper to fetch objects from modules

* lazy import sdxl

* lazy import txt2vid

* lazy import stochastic karras

* fix model imports

* fix bug

* lazy import

* clean up

* clean up

* fixes for tests

* fixes for tests

* clean up

* remove import of torch_utils from utils module

* clean up

* clean up

* fix mistake import statement

* dedicated modules for exporting and loading

* remove testing utils from utils module

* fixes from  merge conflicts

* Update src/diffusers/pipelines/kandinsky2_2/__init__.py

* fix docs

* fix alt diffusion copied from

* fix check dummies

* fix more docs

* remove accelerate import from utils module

* add type checking

* make style

* fix check dummies

* remove torch import from xformers check

* clean up error message

* fixes after upstream merges

* dummy objects fix

* fix tests

* remove unused module import

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

add: tests for t2i adapter training.

* add t2i_example script

* remove in channels logic

* remove comments

* remove use_euler arg

* add requirements

* only use canny example

* use datasets

* comments

* make log_validation consistent with other scripts

* add readme

* fix title in readme

* update check_min_version

* change a few minor things.

* add doc entry

* add: test for t2i adapter training

* remove use_auth_token

* fix: logged info.

* remove tests for now.

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

* Add --vae_precision option to the SDXL pix2pix script so that we have the option of avoiding float32 overhead

* style

---------
Co-authored-by: bghira <bghira@users.github.com>

* Resetting rdm pr

* Fixed styles

* Fixed style

* Moved to rdm folder+fixed slight errors

* Removed config diff

* Started adding tests

* Adding retrieved images

* Fixed faiss import

* Fixed import errors

* Fixing tests

* Added require_faiss

* Updated dependency table

* Attempt solving consistency test

* Fixed truncation and vocab size issue

* Passed common tests

* Finished up cpu testing on pipeline

* Passed all tests locally

* Removed some slow tests

* Removed diffs from test_pipeline_common

* Remove logs

* Removed diffs from test_pipelines_common

* Fixed style

* Fully fixed styles on diffs

* Fixed name

* Proper rename

* Fixed dummies

* Fixed issue with dummyonnx

* Fixed black style

* Fixed dummies

* Changed ordering

* Fixed logging

* Fixing

* Fixing

* quality

* Debugging regex

* Fix dummies with guess

* Fixed typo

* Attempt fix dummies

* black

* ruff

* fixed ordering

* Logging

* Attempt fix

* Attempt fix dummy

* Attempt fixing styles

* Fixed faiss dependency

* Removed unnecessary deprecations

* Finished up main changes

* Added doc

* Passed tests

* Fixed tests

* Remove invisible watermark

* Fixed ruff errors

* Added prompt embed to tests

* Added tests and made retriever an optional component

* Fixed styles

* Made faiss a dependency of pipeline

* Logging

* Fixed dummies

* Make pipeline test work

* Fixed style

* Moved to research projects

* Remove diff

* Fixed style error

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

* Fix potential type conversion errors in SDXL pipelines

* make sure vae stays in fp16

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

* Create masked_stable_diffusion_img2img.py

* add MaskedIm2ImPipeline to readme

* Update README.md

* Increase min accelerate ver to avoid OOM when mixed precision

* Rm re-instantiation of VAE

* Rm casting to float32

* Del unused models and free GPU

* Fix style

* Update textual_inversion.py

fixed safe_path bug in textual inversion training

* Update test_examples.py

update test_textual_inversion for updating saved file's name

* Update textual_inversion.py

fixed some formatting issues

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

* empty PR

* init

* changes

* starting with the pipeline

* stable diff

* prev

* more things, getting started

* more functions

* makeing it more readable

* almost done testing

* var changes

* testing

* device

* device support

* maybe

* device malfunctions

* new new

* register

* testing

* exec does not work

* float

* change info

* change of architecture

* might work

* testing with colab

* more attn atuff

* stupid additions

* documenting and testing

* writing tests

* more docs

* tests and docs

* remove test

* empty PR

* init

* changes

* starting with the pipeline

* stable diff

* prev

* more things, getting started

* more functions

* makeing it more readable

* almost done testing

* var changes

* testing

* device

* device support

* maybe

* device malfunctions

* new new

* register

* testing

* exec does not work

* float

* change info

* change of architecture

* might work

* testing with colab

* more attn atuff

* stupid additions

* documenting and testing

* writing tests

* more docs

* tests and docs

* remove test

* change cross attention

* revert back

* tests

* reverting back to orig

* changes

* test passing

* pipeline changes

* before quality

* quality checks pass

* remove print statements

* doc fixes

* __init__ error something

* update docs, working on dim

* working on encoding

* doc fix

* more fixes

* no more dependent on 512*512

* update docs

* fixes

* test passing

* remove comment

* fixes and migration

* simpler tests

* doc changes

* green CI

* changes

* more docs

* changes

* new images

* to community examples

* selete

* more fixes

* changes

* fix

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

* Optional images variable train_custom_diffusion.py

* Fixed train_custom_diffusion.py

* Revert accidental changes to unet_2d_condition.py

* "Format code with black"