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* [Type Hints] VAE models

* apply suggestions from code review

apply suggestions to also return the return type

* [Type hint] PNDM Schedulers

* ran make style

* updated timesteps type hint

* apply suggestions from code review

* ran make style

* removed unused import

Update unet_blocks.py

fix typo

* [Commands] Add env command

* Apply suggestions from code review

uP

* add void check

* remove void, add types for params

* Use ONNX / Core ML compatible method to broadcast.

Unfortunately `tile` could not be used either, it's still not compatible
with ONNX.

See #284.

* Add comment about why broadcast_to is not used.

Also, apply style to changed files.

* Make sure broadcast remains in same device.

* [Type hint] PNDM pipeline

* ran make style

* Revert "ran make style" wrong black version

Remove joke

* up

* thanks Clau

* finish

* finish

* up

* Fix tqdm and OOM

* tqdm auto

* tqdm is still spamming try to disable it altogether

* rather just set the pipe config, to keep the global tqdm clean

* style

Prose: stable diffusion version v1-3 -> v1-4

The code examples use `v1-4`, but the license text was referring to
`v1-3`.

* add textual inversion script

* make the loop work

* make coarse_loss optional

* save pipeline after training

* add arg pretrained_model_name_or_path

* fix saving

* fix gradient_accumulation_steps

* style

* fix progress bar steps

* scale lr

* add argument to accept style

* remove unused args

* scale lr using num gpus

* load tokenizer using args

* add checks when converting init token to id

* improve commnets and style

* document args

* more cleanup

* fix default adamw arsg

* TextualInversionWrapper -> CLIPTextualInversionWrapper

* fix tokenizer loading

* Use the CLIPTextModel instead of wrapper

* clean dataset

* remove commented code

* fix accessing grads for multi-gpu

* more cleanup

* fix saving on multi-GPU

* init_placeholder_token_embeds

* add seed

* fix flip

* fix multi-gpu

* add utility methods in wrapper

* remove ipynb

* don't use wrapper

* dont pass vae an dunet to accelerate prepare

* bring back accelerator.accumulate

* scale latents

* use only one progress bar for steps

* push_to_hub at the end of training

* remove unused args

* log some important stats

* store args in tensorboard

* pretty comments

* save the trained embeddings

* mobe the script up

* add requirements file

* more cleanup

* fux typo

* begin readme

* style -> learnable_property

* keep vae and unet in eval mode

* address review comments

* address more comments

* removed unused args

* add train command in readme

* update readme

Cancel pending jobs for PRs on new commits

fix grad accum

* Fix nondeterministic tests for GPU runs

* force SD fast tests to the CPU

* Readme sd

* Apply suggestions from code review

* Apply suggestions from code review

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

* Fix flake8 F401 '...' imported but unused

* One more F403

* Changed variable name from "h" to "hidden_states"

Per issue #198 , changed variable name from "h" to "hidden_states" in the forward function only. I am happy to change any other variable names, please advise recommended new names.

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

* add fast tests

* Finish

* [Refactor] Remove set_seed and class attributes

* apply anton's suggestiosn

* fix

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

* up

* update

* make style

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

* make fix-copies

* make style

* make style and new copies
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Anton Lozhkov <anton@huggingface.co>

fix line type