- 19 Mar, 2024 1 commit
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M. Tolga Cangöz authored
Co-authored-by:Sayak Paul <spsayakpaul@gmail.com>
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- 18 Mar, 2024 1 commit
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M. Tolga Cangöz authored
* Fix PyTorch's convention for inplace functions * Fix import structure in __init__.py and update config loading logic in test_config.py * Update configuration access * Fix typos * Trim trailing white spaces * Fix typo in logger name * Revert "Fix PyTorch's convention for inplace functions" This reverts commit f65dc4afcb57ceb43d5d06389229d47bafb10d2d. * Fix typo in step_index property description * Revert "Update configuration access" This reverts commit 8d44e870b8c1ad08802e3e904c34baeca1b598f8. * Revert "Fix import structure in __init__.py and update config loading logic in test_config.py" This reverts commit 2ad5e8bca25aede3b912da22bd57285b598fe171. * Fix typos * Fix typos * Fix typos * Fix a typo: tranform -> transform
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- 27 Feb, 2024 1 commit
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Suraj Patil authored
* Add EDMEulerScheduler * address review comments * fix import * fix test * add tests * add co-author Co-authored-by: @dg845 dgu8957@gmail.com
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- 11 Feb, 2024 1 commit
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dg845 authored
--------- Co-authored-by:
YiYi Xu <yixu310@gmail.com> Co-authored-by:
Dhruv Nair <dhruv.nair@gmail.com>
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- 08 Feb, 2024 1 commit
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Sayak Paul authored
change to 2024
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- 29 Nov, 2023 1 commit
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Suraj Patil authored
* begin model * finish blocks * add_embedding * addition_time_embed_dim * use TimestepEmbedding * fix temporal res block * fix time_pos_embed * fix add_embedding * add conversion script * fix model * up * add new resnet blocks * make forward work * return sample in original shape * fix temb shape in TemporalResnetBlock * add spatio temporal transformers * add vae blocks * fix blocks * update * update * fix shapes in Alphablender and add time activation in res blcok * use new blocks * style * fix temb shape * fix SpatioTemporalResBlock * reuse TemporalBasicTransformerBlock * fix TemporalBasicTransformerBlock * use TransformerSpatioTemporalModel * fix TransformerSpatioTemporalModel * fix time_context dim * clean up * make temb optional * add blocks * rename model * update conversion script * remove UNetMidBlockSpatioTemporal * add in init * remove unused arg * remove unused arg * remove more unsed args * up * up * check for None * update vae * update up/mid blocks for decoder * begin pipeline * adapt scheduler * add guidance scalings * fix norm eps in temporal transformers * add temporal autoencoder * make pipeline run * fix frame decodig * decode in float32 * decode n frames at a time * pass decoding_t to decode_latents * fix decode_latents * vae encode/decode in fp32 * fix dtype in TransformerSpatioTemporalModel * type image_latents same as image_embeddings * allow using differnt eps in temporal block for video decoder * fix default values in vae * pass num frames in decode * switch spatial to temporal for mixing in VAE * fix num frames during split decoding * cast alpha to sample dtype * fix attention in MidBlockTemporalDecoder * fix typo * fix guidance_scales dtype * fix missing activation in TemporalDecoder * skip_post_quant_conv * add vae conversion * style * take guidance scale as input * up * allow passing PIL to export_video * accept fps as arg * add pipeline and vae in init * remove hack * use AutoencoderKLTemporalDecoder * don't scale image latents * add unet tests * clean up unet * clean TransformerSpatioTemporalModel * add slow svd test * clean up * make temb optional in Decoder mid block * fix norm eps in TransformerSpatioTemporalModel * clean up temp decoder * clean up * clean up * use c_noise values for timesteps * use math for log * update * fix copies * doc * upcast vae * update forward pass for gradient checkpointing * make added_time_ids is tensor * up * fix upcasting * remove post quant conv * add _resize_with_antialiasing * fix _compute_padding * cleanup model * more cleanup * more cleanup * more cleanup * remove freeu * remove attn slice * small clean * up * up * remove extra step kwargs * remove eta * remove dropout * remove callback * remove merge factor args * clean * clean up * move to dedicated folder * remove attention_head_dim * docstr and small fix * update unet doc strings * rename decoding_t * correct linting * store c_skip and c_out * cleanup * clean TemporalResnetBlock * more cleanup * clean up vae * clean up * begin doc * more cleanup * up * up * doc * Improve * better naming * better naming * better naming * better naming * better naming * better naming * better naming * better naming * Apply suggestions from code review * Default chunk size to None * add example * Better * Apply suggestions from code review * update doc * Update src/diffusers/pipelines/stable_diffusion_video/pipeline_stable_diffusion_video.py Co-authored-by:
Patrick von Platen <patrick.v.platen@gmail.com> * style * Get torch compile working * up * rename * fix doc * add chunking * torch compile * torch compile * add modelling outputs * torch compile * Improve chunking * Apply suggestions from code review * Update docs/source/en/using-diffusers/svd.md * Close diff tag * remove slicing * resnet docstr * add docstr in resnet * rename * Apply suggestions from code review * update tests * Fix output type latents * fix more * fix more * Update docs/source/en/using-diffusers/svd.md * fix more * add pipeline tests * remove unused arg * clean up * make sure get_scaling receives tensors * fix euler scheduler * fix get_scalings * simply euler for now * remove old test file * use randn_tensor to create noise * fix device for rand tensor * increase expected_max_difference * fix test_inference_batch_single_identical * actually fix test_inference_batch_single_identical * disable test_save_load_float16 * skip test_float16_inference * skip test_inference_batch_single_identical * fix test_xformers_attention_forwardGenerator_pass * Apply suggestions from code review * update StableVideoDiffusionPipelineSlowTests * update image * add diffusers example * fix more --------- Co-authored-by:
apolinário <joaopaulo.passos@gmail.com>
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- 27 Sep, 2023 1 commit
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YiYi Xu authored
* add fast tests for dpm-multi * add more tests * style --------- Co-authored-by:yiyixuxu <yixu310@gmail,com>
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- 11 Sep, 2023 1 commit
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Dhruv Nair authored
* initial commit * move modules to import struct * add dummy objects and _LazyModule * add lazy import to schedulers * clean up unused imports * lazy import on models module * lazy import for schedulers module * add lazy import to pipelines module * lazy import altdiffusion * lazy import audio diffusion * lazy import audioldm * lazy import consistency model * lazy import controlnet * lazy import dance diffusion ddim ddpm * lazy import deepfloyd * lazy import kandinksy * lazy imports * lazy import semantic diffusion * lazy imports * lazy import stable diffusion * move sd output to its own module * clean up * lazy import t2iadapter * lazy import unclip * lazy import versatile and vq diffsuion * lazy import vq diffusion * helper to fetch objects from modules * lazy import sdxl * lazy import txt2vid * lazy import stochastic karras * fix model imports * fix bug * lazy import * clean up * clean up * fixes for tests * fixes for tests * clean up * remove import of torch_utils from utils module * clean up * clean up * fix mistake import statement * dedicated modules for exporting and loading * remove testing utils from utils module * fixes from merge conflicts * Update src/diffusers/pipelines/kandinsky2_2/__init__.py * fix docs * fix alt diffusion copied from * fix check dummies * fix more docs * remove accelerate import from utils module * add type checking * make style * fix check dummies * remove torch import from xformers check * clean up error message * fixes after upstream merges * dummy objects fix * fix tests * remove unused module import --------- Co-authored-by:
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- 23 Aug, 2023 1 commit
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YiYi Xu authored
add self.step_index --------- Co-authored-by:
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- 15 Aug, 2023 1 commit
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Sayak Paul authored
[Pipeline utils] feat: implement push_to_hub for standalone models, schedulers as well as pipelines (#4128) * feat: implement push_to_hub for standalone models. * address PR feedback. * Apply suggestions from code review Co-authored-by:
Lucain <lucainp@gmail.com> * reflect pr feedback. * address another round of deedback. * better handling of kwargs. * add: tests * Apply suggestions from code review Co-authored-by:
ydshieh <2521628+ydshieh@users.noreply.github.com> * fix: tokenizer loading. * fix: json dumping. * move is_staging_test to a better location. * better treatment to tokens. * define repo_id to better handle concurrency * style * explicitly set token * Empty-Commit * move SUER, TOKEN to test * collate org_repo_id * delete repo --------- Co-authored-by:
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- 05 Jul, 2023 2 commits
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dg845 authored
* initial commit * Improve consistency models sampling implementation. * Add CMStochasticIterativeScheduler, which implements the multi-step sampler (stochastic_iterative_sampler) in the original code, and make further improvements to sampling. * Add Unet blocks for consistency models * Add conversion script for Unet * Fix bug in new unet blocks * Fix attention weight loading * Make design improvements to ConsistencyModelPipeline and CMStochasticIterativeScheduler and add initial version of tests. * make style * Make small random test UNet class conditional and set resnet_time_scale_shift to 'scale_shift' to better match consistency model checkpoints. * Add support for converting a test UNet and non-class-conditional UNets to the consistency models conversion script. * make style * Change num_class_embeds to 1000 to better match the original consistency models implementation. * Add support for distillation in pipeline_consistency_models.py. * Improve consistency model tests: - Get small testing checkpoints from hub - Modify tests to take into account "distillation" parameter of ConsistencyModelPipeline - Add onestep, multistep tests for distillation and distillation + class conditional - Add expected image slices for onestep tests * make style * Improve ConsistencyModelPipeline: - Add initial support for class-conditional generation - Fix initial sigma for onestep generation - Fix some sigma shape issues * make style * Improve ConsistencyModelPipeline: - add latents __call__ argument and prepare_latents method - add check_inputs method - add initial docstrings for ConsistencyModelPipeline.__call__ * make style * Fix bug when randomly generating class labels for class-conditional generation. * Switch CMStochasticIterativeScheduler to configuring a sigma schedule and make related changes to the pipeline and tests. * Remove some unused code and make style. * Fix small bug in CMStochasticIterativeScheduler. * Add expected slices for multistep sampling tests and make them pass. * Work on consistency model fast tests: - in pipeline, call self.scheduler.scale_model_input before denoising - get expected slices for Euler and Heun scheduler tests - make Euler test pass - mark Heun test as expected fail because it doesn't support prediction_type "sample" yet - remove DPM and Euler Ancestral tests because they don't support use_karras_sigmas * make style * Refactor conversion script to make it easier to add more model architectures to convert in the future. * Work on ConsistencyModelPipeline tests: - Fix device bug when handling class labels in ConsistencyModelPipeline.__call__ - Add slow tests for onestep and multistep sampling and make them pass - Refactor fast tests - Refactor ConsistencyModelPipeline.__init__ * make style * Remove the add_noise and add_noise_to_input methods from CMStochasticIterativeScheduler for now. * Run python utils/check_copies.py --fix_and_overwrite python utils/check_dummies.py --fix_and_overwrite to make dummy objects for new pipeline and scheduler. * Make fast tests from PipelineTesterMixin pass. * make style * Refactor consistency models pipeline and scheduler: - Remove support for Karras schedulers (only support CMStochasticIterativeScheduler) - Move sigma manipulation, input scaling, denoising from pipeline to scheduler - Make corresponding changes to tests and ensure they pass * make style * Add docstrings and further refactor pipeline and scheduler. * make style * Add initial version of the consistency models documentation. * Refactor custom timesteps logic following DDPMScheduler/IFPipeline and temporarily add torch 2.0 SDPA kernel selection logic for debugging. * make style * Convert current slow tests to use fp16 and flash attention. * make style * Add slow tests for normal attention on cuda device. * make style * Fix attention weights loading * Update consistency model fast tests for new test checkpoints with attention fix. * make style * apply suggestions * Add add_noise method to CMStochasticIterativeScheduler (copied from EulerDiscreteScheduler). * Conversion script now outputs pipeline instead of UNet and add support for LSUN-256 models and different schedulers. * When both timesteps and num_inference_steps are supplied, raise warning instead of error (timesteps take precedence). * make style * Add remaining diffusers model checkpoints for models in the original consistency model release and update usage example. * apply suggestions from review * make style * fix attention naming * Add tests for CMStochasticIterativeScheduler. * make style * Make CMStochasticIterativeScheduler tests pass. * make style * Override test_step_shape in CMStochasticIterativeSchedulerTest instead of modifying it in SchedulerCommonTest. * make style * rename some models * Improve API * rename some models * Remove duplicated block * Add docstring and make torch compile work * More fixes * Fixes * Apply suggestions from code review * Apply suggestions from code review * add more docstring * update consistency conversion script --------- Co-authored-by:
ayushmangal <ayushmangal@microsoft.com> Co-authored-by:
Ayush Mangal <43698245+ayushtues@users.noreply.github.com> Co-authored-by:
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Pedro Cuenca authored
* Add timestep_spacing to DDPM, LMSDiscrete, PNDM. * Remove spurious line. * More easy schedulers. * Add `linspace` to DDIM * Noise sigma for `trailing`. * Add timestep_spacing to DEISMultistepScheduler. Not sure the range is the way it was intended. * Fix: remove line used to debug. * Support timestep_spacing in DPMSolverMultistep, DPMSolverSDE, UniPC * Fix: convert to numpy. * Use sched. defaults when instantiating from_config For params not present in the original configuration. This makes it possible to switch pipeline schedulers even if they use different timestep_spacing (or any other param). * Apply suggestions from code review Co-authored-by:
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- 20 Jun, 2023 1 commit
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Andy Shih authored
* add paradigms parallel sampling pipeline * linting * ran make fix-copies * add paradigms parallel sampling pipeline * linting * ran make fix-copies * Apply suggestions from code review Co-authored-by:
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- 17 Apr, 2023 1 commit
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Patrick von Platen authored
* Better deprecation message * Better deprecation message * Better doc string * Fixes * fix more * fix more * Improve __getattr__ * correct more * fix more * fix * Improve more * more improvements * fix more * Apply suggestions from code review Co-authored-by:
Pedro Cuenca <pedro@huggingface.co> * make style * Fix all rest & add tests & remove old deprecation fns --------- Co-authored-by:
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- 09 Mar, 2023 1 commit
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Patrick von Platen authored
* up * correct some * up * finish
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