GitLab

* add: freeu to the core sdxl pipeline.

* add: freeu to video2video

* add: freeu to the core SD pipelines.

* add: freeu to image variation for sdxl.

* add: freeu to SD ControlNet pipelines.

* add: freeu to SDXL controlnet pipelines.

* add: freu to t2i adapter pipelines.

* make fix-copies.

* Added  mark_step for sdxl to run with pytorch xla. Also updated README with instructions for xla

* adding soft dependency on torch_xla

* fix some styling

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

`jnp.array` is a function, not a type:
https://jax.readthedocs.io/en/latest/_autosummary/jax.numpy.array.html


so it never makes sense to use `jnp.array` in a type annotation.

Presumably the intent was to write `jnp.ndarray` aka `jax.Array`. Change uses of `jnp.array` to `jnp.ndarray`.
Co-authored-by: Peter Hawkins <phawkins@google.com>

* add missing docstrings

* chore: run make quality

* improvement: include docs suggestion by @yiyixuxu

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

Fix [core/GLIGEN]: TypeError when iterating over 0-d tensor with In-painting mode when EulerAncestralDiscreteScheduler is used (#5305)

* fix(gligen_inpaint_pipeline): 🐛

 Wrap the timestep() 0-d tensor in a list to convert to 1-d tensor. This avoids the TypeError caused by trying to directly iterate over a 0-dimensional tensor in the denoising stage

* test(gligen/gligen_text_image): unit test using the EulerAncestralDiscreteScheduler

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Co-authored-by: zhen-hao.chu <zhen-hao.chu@vitrox.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Update pipeline_wuerstchen_prior.py

* prior_num_inference_steps updated

* height, width, num_inference_steps, and guidance_scale synced

* parameters synced

* latent_mean, latent_std, and resolution_multiple synced

* prior_num_inference_steps changed

* Formatted pipeline_wuerstchen_prior.py

* Update src/diffusers/pipelines/wuerstchen/pipeline_wuerstchen_prior.py

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Co-authored-by: Kashif Rasul <kashif.rasul@gmail.com>

Add from single file to StableDiffusionUpscalePipeline and StableDiffusionLatentUpscalePipeline (#5194)

* add from single file

* clean up

* make style

* add single file loading for upscaling

* ✨ Added Fourier filter function to upsample blocks

* 🔧 Update Fourier_filter for float16 support

* ✨ Added UNetFreeUConfig to UNet model for FreeU adaptation 🛠

️

* move unet to its original form and add fourier_filter to torch_utils.

* implement freeU enable mechanism

* implement disable mechanism

* resolution index.

* correct resolution idx condition.

* fix copies.

* no need to use resolution_idx in vae.

* spell out the kwargs

* proper config property

* fix attribution setting

* place unet hasattr properly.

* fix: attribute access.

* proper disable

* remove validation method.

* debug

* debug

* debug

* debug

* debug

* debug

* potential fix.

* add: doc.

* fix copies

* add: tests.

* add: support freeU in SDXL.

* set default value of resolution idx.

* set default values for resolution_idx.

* fix copies

* fix rest.

* fix copies

* address PR comments.

* run fix-copies

* move apply_free_u to utils and other minors.

* introduce support for video (unet3D)

* minor ups

* consistent fix-copies.

* consistent stuff

* fix-copies

* add: rest

* add: docs.

* fix: tests

* fix: doc path

* Apply suggestions from code review
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* style up

* move to techniques.

* add: slow test for sd freeu.

* add: slow test for sd freeu.

* add: slow test for sd freeu.

* add: slow test for sd freeu.

* add: slow test for sd freeu.

* add: slow test for sd freeu.

* add: slow test for video with freeu

* add: slow test for video with freeu

* add: slow test for video with freeu

* style

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* pipline fetcher

* update script

* clean up

* clean up

* clean up

* new pipeline runner

* rename tests to match modules

* test actions in pr

* change runner to gpu

* clean up

* clean up

* clean up

* fix report

* fix reporting

* clean up

* show test stats in failure reports

* give names to jobs

* add lora tests

* split torch cuda tests and add compile tests

* clean up

* fix tests

* change push to run only on main

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

* fix all

* make fix copies

* make fix copies

* Add VAE slicing and tiling methods.

* Switch to using VaeImageProcessing for preprocessing and postprocessing of images.

* Rename the VaeImageProcessor to vae_image_processor to avoid a name clash with the CLIPImageProcessor (image_processor).

* Remove the postprocess() function because we're using a VaeImageProcessor instead.

* Remove UniDiffuserPipeline.decode_image_latents because we're using VaeImageProcessor instead.

* Refactor generating text from text latents into a decode_text_latents method.

* Add enable_full_determinism() to UniDiffuser tests.

* make style

* Add PipelineLatentTesterMixin to UniDiffuserPipelineFastTests.

* Remove enable_model_cpu_offload since it is now part of DiffusionPipeline.

* Rename the VaeImageProcessor instance to self.image_processor for consistency with other pipelines and rename the CLIPImageProcessor instance to clip_image_processor to avoid a name clash.

* Update UniDiffuser conversion script.

* Make safe_serialization configurable in UniDiffuser conversion script.

* Rename image_processor to clip_image_processor in UniDiffuser tests.

* Add PipelineKarrasSchedulerTesterMixin to UniDiffuserPipelineFastTests.

* Add initial test for compiling the UniDiffuser model (not tested yet).

* Update encode_prompt and _encode_prompt to match that of StableDiffusionPipeline.

* Turn off standard classifier-free guidance for now.

* make style

* make fix-copies

* apply suggestions from review

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

Ignore PyTorch, ONNX files when they coexist with Flax weights

* move text encoder changes

* fix

* add comment.

* fix tests

* Update src/diffusers/utils/peft_utils.py

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

* fix

* feedback

* fix xformers lora

* improve

* fix

* fix memory issues

* set _offload_gpu_id

* set gpu offload id

* fix SDXL flax init

* finish

* Fix

Make sure the repo_id is valid before sending it to huggingface_hub to get a more understandable error message.

Re #5110
Co-authored-by: Patrick von Platen <patrick.v.platen@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

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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

* [Doc builder] Ensure slow import for doc builder

* Apply suggestions from code review

* env for doc builder

* fix more

* [Diffusers] Set import to slow as env variable

* fix docs

* fix docs

* Apply suggestions from code review

* Apply suggestions from code review

* fix docs

* fix docs

* fix cpu offload

* fix

* fix

* Update src/diffusers/pipelines/pipeline_utils.py

* make style

* Apply suggestions from code review
Co-authored-by: YiYi Xu <yixu310@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* fix more

* fix more

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Co-authored-by: YiYi Xu <yixu310@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

cpu offload fix for blip diffusion

* support transformer_layers_per block in flax UNet

* add support for text_time additional embeddings to Flax UNet

* rename attention layers for VAE

* add shape asserts when renaming attention layers

* transpose VAE attention layers

* add pipeline flax SDXL code [WIP]

* continue add pipeline flax SDXL code [WIP]

* cleanup

* Working on JIT support

Fixed prompt embedding shapes so they work in parallel mode. Assuming we
always have both text encoders for now, for simplicity.

* Fixing embeddings (untested)

* Remove spurious line

* Shard guidance_scale when jitting.

* Decode images

* Fix sharding

* style

* Refiner UNet can be loaded.

* Refiner / img2img pipeline

* Allow latent outputs from base and latent inputs in refiner

This makes it possible to chain base + refiner without having to use the
vae decoder in the base model, the vae encoder in the refiner, skipping
conversions to/from PIL, and avoiding TPU <-> CPU memory copies.

* Adapt to FlaxCLIPTextModelOutput

* Update Flax XL pipeline to FlaxCLIPTextModelOutput

* make fix-copies

* make style

* add euler scheduler

* Fix import

* Fix copies, comment unused code.

* Fix SDXL Flax imports

* Fix euler discrete begin

* improve init import

* finish

* put discrete euler in init

* fix flax euler

* Fix more

* make style

* correct init

* correct init

* Temporarily remove FlaxStableDiffusionXLImg2ImgPipeline

* correct pipelines

* finish

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Co-authored-by: Martin Müller <martin.muller.me@gmail.com>
Co-authored-by: patil-suraj <surajp815@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* SDXL: update links to refine docs

* make style

* more fixes

* up

* up

* style

* add in setup

* oops

* more changes

* v1 rzfactor CI

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

* few todos

* protect torch import

* style

* fix fuse text encoder

* Update src/diffusers/loaders.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* replace with `recurse_replace_peft_layers`

* keep old modules for BC

* adjustments on `adjust_lora_scale_text_encoder`

* nit

* move tests

* add conversion utils

* remove unneeded methods

* use class method instead

* oops

* use `base_version`

* fix examples

* fix CI

* fix weird error with python 3.8

* fix

* better fix

* style

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

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

* add comment

* Apply suggestions from code review
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* conv2d support for recurse remove

* added docstrings

* more docstring

* add deprecate

* revert

* try to fix merge conflicts

* v1 tests

* add new decorator

* add saving utilities test

* adapt tests a bit

* add save / from_pretrained tests

* add saving tests

* add scale tests

* fix deps tests

* fix lora CI

* fix tests

* add comment

* fix

* style

* add slow tests

* slow tests pass

* style

* Update src/diffusers/utils/import_utils.py
Co-authored-by: Benjamin Bossan <BenjaminBossan@users.noreply.github.com>

* Apply suggestions from code review
Co-authored-by: Benjamin Bossan <BenjaminBossan@users.noreply.github.com>

* circumvents pattern finding issue

* left a todo

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

* update hub path

* add lora workflow

* fix

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Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Benjamin Bossan <BenjaminBossan@users.noreply.github.com>

Add missing parenthesis in the sample code of BLIP Diffusion

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Co-authored-by: yiyixuxu <yixu310@gmail,com>

fix and add tests
Co-authored-by: yiyixuxu <yixu310@gmail,com>

* Add BLIP Diffusion skeleton

* Add other model components

* Add BLIP2, need to change it for now

* Fix pipeline imports

* Load pretrained ViT

* Make qformer fwd pass same

* Replicate fwd passes

* Fix device bug

* Add accelerate functions

* Remove extra functions from Blip2

* Minor bug

* Integrate initial review changes

* Refactoring

* Refactoring

* Refactor

* Add controlnet

* Refactor

* Update conversion script

* Add image processor

* Shift postprocessing to ImageProcessor

* Refactor

* Fix device

* Add fast tests

* Update conversion script

* Fix checkpoint conversion script

* Integrate review changes

* Integrate reivew changes

* Remove unused functions from test

* Reuse HF image processor in Cond image

* Create new BlipImageProcessor based on transfomers

* Fix image preprocessor

* Minor

* Minor

* Add canny preprocessing

* Fix controlnet preprocessing

* Fix blip diffusion test

* Add controlnet test

* Add initial doc strings

* Integrate review changes

* Refactor

* Update examples

* Remove DDIM comments

* Add copied from for prepare_latents

* Add type anotations

* Add docstrings

* Do black formatting

* Add batch support

* Make tests pass

* Make controlnet tests pass

* Black formatting

* Fix progress bar

* Fix some licensing comments

* Fix imports

* Refactor controlnet

* Make tests faster

* Edit examples

* Black formatting/Ruff

* Add doc

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

* Move controlnet pipeline

* Make tests faster

* Fix imports

* Fix formatting

* Fix make errors

* Fix make errors

* Minor

* Add suggested doc changes
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Edit docs

* Fix 16 bit loading

* Update examples

* Edit toctree

* Update docs/source/en/api/pipelines/blip_diffusion.md
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Minor

* Add tips

* Edit examples

* Update model paths

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

* core: add support for clip ckip to SDXL

* add clip_skip support to the rest of the pipeline.

* Empty-Commit

* [SDXL] Make sure multi batch prompt embeds works

* [SDXL] Make sure multi batch prompt embeds works

* improve more

* improve more

* Apply suggestions from code review