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* [Utils] Correct custom init sort

* [Utils] Correct custom init sort

* [Utils] Correct custom init sort

* add type checking

* fix custom init sort

* fix test

* fix tests

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

* [Draft] Refactor model offload

* [Draft] Refactor model offload

* Apply suggestions from code review

* cpu offlaod updates

* remove model cpu offload from individual pipelines

* add hook to offload models to cpu

* clean up

* model offload

* add model cpu offload string

* make style

* clean up

* fixes for offload issues

* fix tests issues

* resolve merge conflicts

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

* make style

* Update src/diffusers/pipelines/latent_diffusion/pipeline_latent_diffusion.py

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

* 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>

* 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

* create general cpu offload & execution device

* Remove boiler plate

* finish

* kp

* Correct offload more pipelines

* up

* Update src/diffusers/pipelines/pipeline_utils.py

* make style

* up

* [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

* before running make style

* remove left overs from flake8

* finish

* make fix-copies

* final fix

* more fixes

* 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>

* [Repro] Correct reproducability

* up

* up

* uP

* up

* need better image

* allow conversion from no state dict checkpoints

* up

* up

* up

* up

* check tensors

* check tensors

* check tensors

* check tensors

* next try

* up

* up

* better name

* up

* up

* Apply suggestions from code review

* correct more

* up

* replace all torch randn

* fix

* correct

* correct

* finish

* fix more

* up

* 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>

[Batched Generators] This PR adds generators that are useful to make batched generation fully reproducible  (#1718)

* [Batched Generators] all batched generators

* up

* up

* up

* up

* up

* up

* up

* up

* up

* up

* up

* up

* up

* up

* up

* up

* hey

* up again

* fix tests

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

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

upgrade version

* [SD] Make sure batched input works correctly

* uP

* uP

* up

* up

* uP

* up

* fix mask stuff

* up

* uP

* more up

* up

* uP

* up

* finish

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

* [WIP] Standardize fast pipeline tests with PipelineTestMixin

* refactor the sd tests a bit

* add more common tests

* add xformers

* add progressbar test

* cleanup

* upd fp16

* CycleDiffusionPipelineFastTests

* DanceDiffusionPipelineFastTests

* AltDiffusionPipelineFastTests

* StableDiffusion2PipelineFastTests

* StableDiffusion2InpaintPipelineFastTests

* StableDiffusionImageVariationPipelineFastTests

* StableDiffusionImg2ImgPipelineFastTests

* StableDiffusionInpaintPipelineFastTests

* remove unused mixins

* quality

* add missing inits

* try to fix mps tests

* fix mps tests

* add mps warmups

* skip for some pipelines

* style

* Update tests/test_pipelines_common.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* fix non square images with UNet2DModel and DDIM/DDPM pipelines

* fix unet_2d `sample_size` docstring

* update pipeline tests for unet uncond
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* [Tests] Fix mps+generator fast tests

* mps for Euler

* retry

* warmup issue again?

* fix reproducible initial noise

* Revert "fix reproducible initial noise"

This reverts commit f300d05cb9782ed320064a0c58577a32d4139e6d.

* fix reproducible initial noise

* fix device

* Match the generator device to the pipeline for DDPM and DDIM

* style

* fix

* update values

* fix fast tests

* trigger slow tests

* deprecate

* last value fixes

* mps fixes

add licenses

* Fix equality test for ddim and ddpm

* add docs for use_clipped_model_output in DDIM

* fix inline comment

* reorder imports in test_pipelines.py

* Ignore use_clipped_model_output if scheduler doesn't take it

* pytorch only schedulers

* fix style

* remove match_shape

* pytorch only ddpm

* remove SchedulerMixin

* remove numpy from karras_ve

* fix types

* remove numpy from lms_discrete

* remove numpy from pndm

* fix typo

* remove mixin and numpy from sde_vp and ve

* remove remaining tensor_format

* fix style

* sigmas has to be torch tensor

* removed set_format in readme

* remove set format from docs

* remove set_format from pipelines

* update tests

* fix typo

* continue to use mixin

* fix imports

* removed unsed imports

* match shape instead of assuming image shapes

* remove import typo

* update call to add_noise

* use math instead of numpy

* fix t_index

* removed commented out numpy tests

* timesteps needs to be discrete

* cast timesteps to int in flax scheduler too

* fix device mismatch issue

* small fix

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

* Remove deprecated `torch_device` kwarg.

* Remove unused imports.

* Fix typos

* Add a typo check action

* Fix a bug

* Changed to manual typo check currently

Ref: https://github.com/huggingface/diffusers/pull/483#pullrequestreview-1104468010

Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

* Removed a confusing message

* Renamed "nin_shortcut" to "in_shortcut"

* Add memo about NIN
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

* [Outputs] Improve syntax

* improve more

* fix docstring return

* correct all

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

* ddim docs

for issue #293

* space

* type hints

* Apply suggestions from code review
Co-authored-by: Anton Lozhkov <anton@huggingface.co>

* add outputs for models

* add for pipelines

* finish schedulers

* better naming

* adapt tests as well

* replace dict access with . access

* make schedulers works

* finish

* correct readme

* make  bcp compatible

* up

* small fix

* finish

* more fixes

* more fixes

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

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

* Adapt model outputs

* Apply more suggestions

* finish examples

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

* Refactor progress bar of pipeline __call__

* Make any tqdm configs available

* remove init

* add some tests

* remove file

* finish

* make style

* improve progress bar test
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Implement `pipeline.to(device)`

* DiffusionPipeline.to() decides best device on None.

* Breaking change: torch_device removed from __call__

`pipeline.to()` now has PyTorch semantics.

* Use kwargs and deprecation notice
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Apply torch_device compatibility to all pipelines.

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

* Revive Make utils

* Add datasets for training too

* up

* change model name

* renaming

* more changes

* up

* up

* up

* save checkpoint

* finish api / naming

* finish config renaming

* rename all weights

* finish really

* finish

* up