* make tests deterministic
* run slow tests
* prepare for testing
* finish
* refactor
* add print statements
* finish more
* correct some test failures
* more fixes
* set up to correct tests
* more corrections
* up
* fix more
* more prints
* add
* up
* up
* up
* uP
* uP
* more fixes
* uP
* up
* up
* up
* up
* fix more
* up
* up
* clean tests
* up
* up
* up
* more fixes
* Apply suggestions from code review
Co-authored-by: Suraj Patil <surajp815@gmail.com>
* make
* correct
* finish
* finish
Co-authored-by: Suraj Patil <surajp815@gmail.com>
* from_flax
* oops
* oops
* make style with pip install -e ".[dev]"
* oops
* now code quality happy 😋
* allow_patterns += FLAX_WEIGHTS_NAME
* Update src/diffusers/pipelines/pipeline_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/pipeline_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/pipeline_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/pipeline_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/models/modeling_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/pipeline_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* for test
* bye bye is_flax_available()
* oops
* Update src/diffusers/models/modeling_pytorch_flax_utils.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update src/diffusers/models/modeling_pytorch_flax_utils.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update src/diffusers/models/modeling_pytorch_flax_utils.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update src/diffusers/models/modeling_utils.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update src/diffusers/models/modeling_utils.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* make style
* add test
* finihs
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* move files a bit
* more refactors
* fix more
* more fixes
* fix more onnx
* make style
* upload
* fix
* up
* fix more
* up again
* up
* small fix
* Update src/diffusers/__init__.py
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* correct
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Add parameter safe_serialization to DiffusionPipeline.save_pretrained
* Add option safe_serialization on ModelMixin.save_pretrained
* Add test test_save_safe_serialization
* Black
* Re-trigger the CI
* Fix doc-builder
* Validate files are saved as safetensor in test_save_safe_serialization
* feat: switch core pipelines to use image arg
* test: update tests for core pipelines
* feat: switch examples to use image arg
* docs: update docs to use image arg
* style: format code using black and doc-builder
* fix: deprecate use of init_image in all pipelines
* Add heun
* Finish first version of heun
* remove bogus
* finish
* finish
* improve
* up
* up
* fix more
* change progress bar
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py
* finish
* up
* up
* up
* [Proposal] Support loading from safetensors if file is present.
* Style.
* Fix.
* Adding some test to check loading logic.
+ modify download logic to not download pytorch file if not necessary.
* Fixing the logic.
* Adressing comments.
* factor out into a function.
* Remove dead function.
* Typo.
* Extra fetch only if safetensors is there.
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Adapt ddpm, ddpmsolver to prediction_type.
* Deprecate predict_epsilon in __init__.
* Bring FlaxDDIMScheduler up to date with DDIMScheduler.
* Set prediction_type as an ivar for consistency.
* Convert pipeline_ddpm
* Adapt tests.
* Adapt unconditional training script.
* Adapt BitDiffusion example.
* Add missing kwargs in dpmsolver_multistep
* Ugly workaround to accept deprecated predict_epsilon when loading
schedulers using from_pretrained.
* make style
* Remove import no longer in use.
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Use config.prediction_type everywhere
* Add a couple of Flax prediction type tests.
* make style
* fix register deprecated arg
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* fix non square images with UNet2DModel and DDIM/DDPM pipelines
* fix unet_2d `sample_size` docstring
* update pipeline tests for unet uncond
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* add conversion script for vae
* uP
* uP
* more changes
* push
* up
* finish again
* up
* up
* up
* up
* finish
* up
* uP
* up
* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Anton Lozhkov <anton@huggingface.co>
Co-authored-by: Suraj Patil <surajp815@gmail.com>
* up
* up
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Anton Lozhkov <anton@huggingface.co>
Co-authored-by: Suraj Patil <surajp815@gmail.com>
* Match the generator device to the pipeline for DDPM and DDIM
* style
* fix
* update values
* fix fast tests
* trigger slow tests
* deprecate
* last value fixes
* mps fixes
* [Scheduler] Move predict epsilon to init
* up
* uP
* uP
* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* up
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Schedulers: don't use float64 on mps
* Test set_timesteps() on device (float schedulers).
* SD pipeline: use device in set_timesteps.
* SD in-painting pipeline: use device in set_timesteps.
* Tests: fix mps crashes.
* Skip test_load_pipeline_from_git on mps.
Not compatible with float16.
* Use device.type instead of str in Euler schedulers.
* make accelerate hard dep
* default fast init
* move params to cpu when device map is None
* handle device_map=None
* handle torch < 1.9
* remove device_map="auto"
* style
* add accelerate in torch extra
* remove accelerate from extras["test"]
* raise an error if torch is available but not accelerate
* update installation docs
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* improve defautl loading speed even further, allow disabling fats loading
* address review comments
* adapt the tests
* fix test_stable_diffusion_fast_load
* fix test_read_init
* temp fix for dummy checks
* Trigger Build
* Apply suggestions from code review
Co-authored-by: Anton Lozhkov <anton@huggingface.co>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Anton Lozhkov <anton@huggingface.co>
* Fix equality test for ddim and ddpm
* add docs for use_clipped_model_output in DDIM
* fix inline comment
* reorder imports in test_pipelines.py
* Ignore use_clipped_model_output if scheduler doesn't take it
* add method to enable cuda with minimal gpu usage to stable diffusion
* add test to minimal cuda memory usage
* ensure all models but unet are onn torch.float32
* move to cpu_offload along with minor internal changes to make it work
* make it test against accelerate master branch
* coming back, its official: I don't know how to make it test againt the master branch from accelerate
* make it install accelerate from master on tests
* go back to accelerate>=0.11
* undo prettier formatting on yml files
* undo prettier formatting on yml files againn
* begin pipe
* add new pipeline
* add tests
* correct fast test
* up
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_inpaint.py
* Update tests/test_pipelines.py
* up
* up
* make style
* add fp16 test
* doc, comments
* up
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Anton Lozhkov <anton@huggingface.co>
Patrick von Platen