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* Helpful exception if inference steps not set in schedulers (#263)

* Apply suggestions from codereview by patrickvonplaten

* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Support K-LMS in img2img

* Apply review suggestions

* Fixed add_noise in LMSDiscreteScheduler

* Linting

* Update src/diffusers/schedulers/scheduling_lms_discrete.py
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

add add_noise method in more schedulers

* Revive Make utils

* Add datasets for training too

* test LMS with LDM

* test LMS with LDM

* Interchangeable sigma and timestep. Added dummy objects

* Debug

* cuda generator

* Fix derivatives

* Update tests

* Rename Lms->LMS

* [PNDM] Stable diffusino

* finish

* [Half precision] Make sure half-precision is correct

* Update src/diffusers/models/unet_2d.py

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py

* correct some tests

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

* finalize

* finish
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* add stable diffusion pipeline

* get rid of multiple if/else

* batch_size is unused

* add type hints

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py

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

use inspect instead of unused kwargs

* karras + VE, not flexible yet

* Fix inputs incompatibility with the original unet

* Roll back sigma scaling

* Apply suggestions from code review

* Old comment

* Fix doc

* Extented the ability of ddpm scheduler
to utilize model that also predict the variance.

* Update src/diffusers/schedulers/scheduling_ddpm.py
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

* Typos

* Credits and roadmap

* Second version

* work in progress, fixing tests for numpy and make deterministic

* make tests pass via pytorch

* make pytorch == numpy test cleaner

* change default tensor format pndm --> pt

* organize PNDM tests, begin API change

* clean timestep API PNDM

* update pipeline PNDM

* fix typo

* API clean round 2

* small nit

* Add a decorator for register_to_config

* All models and test

* clean ddpm api to match ddim

* correct ve sde class

* update pipeline API for ve sde

* make style

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

* improve comments for sde_ve scheduler, init tests

* more comments, tweaking pipelines

* timesteps --> num_training_timesteps, some comments

* merge cpu test, add m1 data

* fix scheduler tests with num_train_timesteps

* make np compatible, add tests for sde ve

* minor default variable fixes

* make style and fix-copies
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* finish

* up

* add a metrics logger

* fix LatentDiffusionUncondPipeline

* add VQModel in init

* add image logging to tensorboard

* switch manual templates to the modelcards package

* hide ldm example
Co-authored-by: patil-suraj <surajp815@gmail.com>