GitLab

* 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>