* [CI] Add Apple M1 tests
* setup-python
* python build
* conda install
* remove branch
* only 3.8 is built for osx-arm
* try fetching prebuilt tokenizers
* use user cache
* update shells
* Reports and cleanup
* -> MPS
* Disable parallel tests
* Better naming
* investigate worker crash
* return xdist
* restart
* num_workers=2
* still crashing?
* faulthandler for segfaults
* faulthandler for segfaults
* remove restarts, stop on segfault
* torch version
* change installation order
* Use pre-RC version of PyTorch.
To be updated when it is released.
* Skip crashing test on MPS, add new one that works.
* Skip cuda tests in mps device.
* Actually use generator in test.
I think this was a typo.
* make style
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Bump to 0.6.0.dev0
* Deprecate tensor_format and .samples
* style
* upd
* upd
* style
* sample -> images
* Update src/diffusers/schedulers/scheduling_ddpm.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/schedulers/scheduling_ddim.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/schedulers/scheduling_karras_ve.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/schedulers/scheduling_lms_discrete.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/schedulers/scheduling_pndm.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/schedulers/scheduling_sde_ve.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/schedulers/scheduling_sde_vp.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Remove set_format in Flax pipeline.
* Remove DummyChecker.
* Run safety_checker in pipeline.
* Don't pmap on every call.
We could have decorated `generate` with `pmap`, but I wanted to keep it
in case someone wants to invoke it in non-parallel mode.
* Remove commented line
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Replicate outside __call__, prepare for optional jitting.
* Remove unnecessary clipping.
As suggested by @kashif.
* Do not jit unless requested.
* Send all args to generate.
* make style
* Remove unused imports.
* Fix docstring.
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Give more customizable options for safety checker
* Apply suggestions from code review
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py
* Finish
* make style
* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* up
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Add diffusers version and pipeline class to the Hub UA
* Fallback to class name for pipelines
* Update src/diffusers/modeling_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/modeling_flax_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Remove autoclass
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* [Dummy imports] Better error message
* Test: load pipeline with LMS scheduler.
Fails with a cryptic message if scipy is not installed.
* Correct
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* mps: alt. implementation for repeat_interleave
* style
* Bump mps version of PyTorch in the documentation.
* Apply suggestions from code review
Co-authored-by: Suraj Patil <surajp815@gmail.com>
* Simplify: do not check for device.
* style
* Fix repeat dimensions:
- The unconditional embeddings are always created from a single prompt.
- I was shadowing the batch_size var.
* Split long lines as suggested by Suraj.
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>
* pass norm_num_groups param and add tests
* set resnet_groups for FlaxUNetMidBlock2D
* fixed docstrings
* fixed typo
* using is_flax_available util and created require_flax decorator
* begin text2image script
* loading the datasets, preprocessing & transforms
* handle input features correctly
* add gradient checkpointing support
* fix output names
* run unet in train mode not text encoder
* use no_grad instead of freezing params
* default max steps None
* pad to longest
* don't pad when tokenizing
* fix encode on multi gpu
* fix stupid bug
* add random flip
* add ema
* fix ema
* put ema on cpu
* improve EMA model
* contiguous_format
* don't warp vae and text encode in accelerate
* remove no_grad
* use randn_like
* fix resize
* improve few things
* log epoch loss
* set log level
* don't log each step
* remove max_length from collate
* style
* add report_to option
* make scale_lr false by default
* add grad clipping
* add an option to use 8bit adam
* fix logging in multi-gpu, log every step
* more comments
* remove eval for now
* adress review comments
* add requirements file
* begin readme
* begin readme
* fix typo
* fix push to hub
* populate readme
* update readme
* remove use_auth_token from the script
* address some review comments
* better mixed precision support
* remove redundant to
* create ema model early
* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* better description for train_data_dir
* add diffusers in requirements
* update dataset_name_mapping
* update readme
* add inference example
Co-authored-by: anton-l <anton@huggingface.co>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Support deepspeed
* Dreambooth DeepSpeed documentation
* Remove unnecessary casts, documentation
Due to recent commits some casts to half precision are not necessary
anymore.
Mention that DeepSpeed's version of Adam is about 2x faster.
* Review comments
Hamish Friedlander