* add UniPC scheduler
* add the return type to the functions
* code quality check
* add tests
* finish docs
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* add store and restore() methods to EMAModel.
* Update src/diffusers/training_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* make style with doc builder
* remove explicit listing.
* Apply suggestions from code review
Co-authored-by: Will Berman <wlbberman@gmail.com>
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* chore: better variable naming.
* better treatment of temp_stored_params
Co-authored-by: patil-suraj <surajp815@gmail.com>
* make style
* remove temporary params from earth 🌎
* make fix-copies.
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Will Berman <wlbberman@gmail.com>
Co-authored-by: patil-suraj <surajp815@gmail.com>
* add: support for BLIP generation.
* add: support for editing synthetic images.
* remove unnecessary comments.
* add inits and run make fix-copies.
* version change of diffusers.
* fix: condition for loading the captioner.
* default conditions_input_image to False.
* guidance_amount -> cross_attention_guidance_amount
* fix inputs to check_inputs()
* fix: attribute.
* fix: prepare_attention_mask() call.
* debugging.
* better placement of references.
* remove torch.no_grad() decorations.
* put torch.no_grad() context before the first denoising loop.
* detach() latents before decoding them.
* put deocding in a torch.no_grad() context.
* add reconstructed image for debugging.
* no_grad(0
* apply formatting.
* address one-off suggestions from the draft PR.
* back to torch.no_grad() and add more elaborate comments.
* refactor prepare_unet() per Patrick's suggestions.
* more elaborate description for .
* formatting.
* add docstrings to the methods specific to pix2pix zero.
* suspecting a redundant noise prediction.
* needed for gradient computation chain.
* less hacks.
* fix: attention mask handling within the processor.
* remove attention reference map computation.
* fix: cross attn args.
* fix: prcoessor.
* store attention maps.
* fix: attention processor.
* update docs and better treatment to xa args.
* update the final noise computation call.
* change xa args call.
* remove xa args option from the pipeline.
* add: docs.
* first test.
* fix: url call.
* fix: argument call.
* remove image conditioning for now.
* 🚨 add: fast tests.
* explicit placement of the xa attn weights.
* add: slow tests 🐢
* fix: tests.
* edited direction embedding should be on the same device as prompt_embeds.
* debugging message.
* debugging.
* add pix2pix zero pipeline for a non-deterministic test.
* debugging/
* remove debugging message.
* make caption generation _
* address comments (part I).
* address PR comments (part II)
* fix: DDPM test assertion.
* refactor doc.
* address PR comments (part III).
* fix: type annotation for the scheduler.
* apply styling.
* skip_mps and add note on embeddings in the docs.
* add total number checkpoints to training scripts
* Update examples/dreambooth/train_dreambooth.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
There isn't a space between the "Scope" paragraph and "Ethical Guidelines", here: https://huggingface.co/docs/diffusers/main/en/conceptual/ethical_guidelines , yet I can't see that in the preview. In this PR, I'm simply adding some spaces in the hopes that it resolves the issue.....
* initial docs about KarrasDiffusionSchedulers
* typo
* grammer
* Update docs/source/en/api/schedulers/overview.mdx
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* do not list the schedulers explicitly
---------
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Log Unconditional Image Generation Samples to WandB
* Check for wandb installation and parity between onnxruntime script
* Log epoch to wandb
* Check for tensorboard logger early on
* style fixes
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* pipeline_variant
* Add docs for when clip_stats_path is specified
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_unclip.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_unclip.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_unclip_img2img.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_unclip_img2img.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* prepare_latents # Copied from re: @patrickvonplaten
* NoiseAugmentor->ImageNormalizer
* stable_unclip_prior default to None re: @patrickvonplaten
* prepare_prior_extra_step_kwargs
* prior denoising scale model input
* {DDIM,DDPM}Scheduler -> KarrasDiffusionSchedulers re: @patrickvonplaten
* docs
* Update docs/source/en/api/pipelines/stable_unclip.mdx
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* unet check length input
* prep test file for changes
* correct all tests
* clean up
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* [LoRA] Freezing the model weights
Freeze the model weights since we don't need to calculate grads for them.
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Apply suggestions from code review
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Resolves ValueError: `num_inference_steps`: 1000 cannot be larger than `self.config.train_timesteps`: 50 as the unet model trained with this scheduler can only handle maximal 50 timesteps.
* EMA: fix `state_dict()` & add `cur_decay_value`
* EMA: fix a bug in `load_state_dict()`
'float' object (`state_dict["power"]`) has no attribute 'get'.
* del train_unconditional_ort.py
* Quality check and adding tokenizer
* Adapted stable diffusion to mixed precision+finished up style fixes
* Fixed based on patrick's review
* Fixed oom from number of validation images
* Removed unnecessary np.array conversion
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* better accelerated saving
* up
* finish
* finish
* uP
* up
* up
* fix
* Apply suggestions from code review
* correct ema
* Remove @
* up
* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update docs/source/en/training/dreambooth.mdx
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
---------
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
