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Replace message with empty backquotes.

This was part of #733, I was too slow to review :)

remove use_auth_token

* up

* uP

* uP

* make style

* Apply suggestions from code review

* up

* finish

* Removing `autocast` for `35-25% speedup`.

* iQuality

* Adding a slow test.

* Fixing mps noise generation.

* Raising error on wrong device, instead of just casting on behalf of user.

* Quality.

* fix merge
Co-authored-by: Nouamane Tazi <nouamane98@gmail.com>

* init

* improve add_noise

* [debug start] run slow test

* [debug end]

* quick revert

* Add docstrings and warnings + API tests

* Make the warning less spammy

* pytorch timesteps

* style

* get rid of if-else

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

* Avoid negative strides for tensors

* Changed not to make torch.tensor

* Removed a needless copy

using already created `Path` in dataset

* fix accelerate for testing

* fix copies

* uP

* renamed single letter variables

* renamed x to meaningful variable in resnet.py

Hello @patil-suraj can you verify it
Thanks

* Reformatted using black

* renamed x to meaningful variable in resnet.py

Hello @patil-suraj can you verify it
Thanks

* reformatted the files

* modified unboundlocalerror in line 374

* removed referenced before error

* renamed single variable x -> hidden_state, p-> pad_value
Co-authored-by: Nikhil A V <nikhilav@Nikhils-MacBook-Pro.local>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>

fix clip_grad_norm_

Remove comments no longer appropriate.

There were casting operations before, they are now gone.

* Fix import if PyTorch is not installed.

* Style (blank line)

* Add an argument "negative_prompt"

* Fix argument order

* Fix to use TypeError instead of ValueError

* Removed needless batch_size multiplying

* Fix to multiply by batch_size

* Add truncation=True for long negative prompt

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

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

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

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

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_img2img.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

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

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

* Fix styles

* Renamed ucond_tokens to uncond_tokens

* Added description about "negative_prompt"
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Fix typos

* Update examples/dreambooth/train_dreambooth.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* add accelerate to load models with smaller memory footprint

* remove low_cpu_mem_usage as it is reduntant

* move accelerate init weights context to modelling utils

* add test to ensure results are the same when loading with accelerate

* add tests to ensure ram usage gets lower when using accelerate

* move accelerate logic to single snippet under modelling utils and remove it from configuration utils

* format code using to pass quality check

* fix imports with isor

* add accelerate to test extra deps

* only import accelerate if device_map is set to auto

* move accelerate availability check to diffusers import utils

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

* Update links in schedulers README.md

* Update src/diffusers/schedulers/README.md
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

fix docstring

fixes #709

* Conversion script

* ran black

* ran isort

* remove unused import

* map location so everything gets loaded onto CPU before conversion

* ran black again

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

* [Utils] Add deprecate function

* up

* up

* uP

* up

* up

* up

* up

* uP

* up

* fix

* up

* move to deprecation utils file

* fix

* fix

* fix more

* [CI] Localize the HF cache

* pip cache

* de-env

* refactor matrix

* fix fast cache

* less onnx steps

* revert

* revert pip cache

* revert pip cache

* remove debugging trigger

* Don't use `load_state_dict` if torch is not installed.

* Define `SchedulerOutput` to use torch or flax arrays.

* Don't import LMSDiscreteScheduler without torch.

* Create distinct FlaxSchedulerOutput.

* Additional changes required for FlaxSchedulerMixin

* Do not import torch pipelines in Flax.

* Revert "Define `SchedulerOutput` to use torch or flax arrays."

This reverts commit f653140134b74d9ffec46d970eb46925fe3a409d.

* Prefix Flax scheduler outputs for consistency.

* make style

* FlaxSchedulerOutput is now a dataclass.

* Don't use f-string without placeholders.

* Add blank line.

* Style (docstrings)

Fixed type annotations on StableDiffusionPipeline::__call__

* Flax: add shape argument to set_timesteps

* style

fix applying clip grad norm

* Add callback parameters for Stable Diffusion pipelines
Signed-off-by: James R T <jamestiotio@gmail.com>

* Lint code with `black --preview`
Signed-off-by: James R T <jamestiotio@gmail.com>

* Refactor callback implementation for Stable Diffusion pipelines

* Fix missing imports
Signed-off-by: James R T <jamestiotio@gmail.com>

* Fix documentation format
Signed-off-by: James R T <jamestiotio@gmail.com>

* Add kwargs parameter to standardize with other pipelines
Signed-off-by: James R T <jamestiotio@gmail.com>

* Modify Stable Diffusion pipeline callback parameters
Signed-off-by: James R T <jamestiotio@gmail.com>

* Remove useless imports
Signed-off-by: James R T <jamestiotio@gmail.com>

* Change types for timestep and onnx latents

* Fix docstring style

* Return decode_latents and run_safety_checker back into __call__

* Remove unused imports

* Add intermediate state tests for Stable Diffusion pipelines
Signed-off-by: James R T <jamestiotio@gmail.com>

* Fix intermediate state tests for Stable Diffusion pipelines
Signed-off-by: James R T <jamestiotio@gmail.com>
Signed-off-by: James R T <jamestiotio@gmail.com>

* Fix BibText citation

* Update README.md

* revert using baddbmm in attention
- to fix `test_stable_diffusion_memory_chunking` test

* styling

refactor: update ldm-bert `config.json` url
Signed-off-by: Ryan Russell <git@ryanrussell.org>
Signed-off-by: Ryan Russell <git@ryanrussell.org>

* Allow resolutions that are not multiples of 64

* ran black

* fix bug

* add test

* more explanation

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

* initial commit

* make UNet stream capturable

* try to fix noise_pred value

* remove cuda graph and keep NB

* non blocking unet with PNDMScheduler

* make timesteps np arrays for pndm scheduler
because lists don't get formatted to tensors in `self.set_format`

* make max async in pndm

* use channel last format in unet

* avoid moving timesteps device in each unet call

* avoid memcpy op in `get_timestep_embedding`

* add `channels_last` kwarg to `DiffusionPipeline.from_pretrained`

* update TODO

* replace `channels_last` kwarg with `memory_format` for more generality

* revert the channels_last changes to leave it for another PR

* remove non_blocking when moving input ids to device

* remove blocking from all .to() operations at beginning of pipeline

* fix merging

* fix merging

* model can run in other precisions without autocast

* attn refactoring

* Revert "attn refactoring"

This reverts commit 0c70c0e189cd2c4d8768274c9fcf5b940ee310fb.

* remove restriction to run conv_norm in fp32

* use `baddbmm` instead of `matmul`for better in attention for better perf

* removing all reshapes to test perf

* Revert "removing all reshapes to test perf"

This reverts commit 006ccb8a8c6bc7eb7e512392e692a29d9b1553cd.

* add shapes comments

* hardcore whats needed for jitting

* Revert "hardcore whats needed for jitting"

This reverts commit 2fa9c698eae2890ac5f8e367ca80532ecf94df9a.

* Revert "remove restriction to run conv_norm in fp32"

This reverts commit cec592890c32da3d1b78d38b49e4307aedf459b9.

* revert using baddmm in attention's forward

* cleanup comment

* remove restriction to run conv_norm in fp32. no quality loss was noticed

This reverts commit cc9bc1339c998ebe9e7d733f910c6d72d9792213.

* add more optimizations techniques to docs

* Revert "add shapes comments"

This reverts commit 31c58eadb8892f95478cdf05229adf678678c5f4.

* apply suggestions

* make quality

* apply suggestions

* styling

* `scheduler.timesteps` are now arrays so we dont need .to()

* remove useless .type()

* use mean instead of max in `test_stable_diffusion_inpaint_pipeline_k_lms`

* move scheduler timestamps to correct device if tensors

* add device to `set_timesteps` in LMSD scheduler

* `self.scheduler.set_timesteps` now uses device arg for schedulers that accept it

* quick fix

* styling

* remove kwargs from schedulers `set_timesteps`

* revert to using max in K-LMS inpaint pipeline test

* Revert "`self.scheduler.set_timesteps` now uses device arg for schedulers that accept it"

This reverts commit 00d5a51e5c20d8d445c8664407ef29608106d899.

* move timesteps to correct device before loop in SD pipeline

* apply previous fix to other SD pipelines

* UNet now accepts tensor timesteps even on wrong device, to avoid errors
- it shouldnt affect performance if timesteps are alrdy on correct device
- it does slow down performance if they're on the wrong device

* fix pipeline when timesteps are arrays with strides

renamed x to hidden_states