- 12 Sep, 2023 1 commit
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Patrick von Platen authored
* [Utils] Correct custom init sort * [Utils] Correct custom init sort * [Utils] Correct custom init sort * add type checking * fix custom init sort * fix test * fix tests --------- Co-authored-by:Dhruv Nair <dhruv.nair@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:Patrick von Platen <patrick.v.platen@gmail.com>
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- 06 Sep, 2023 1 commit
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Kashif Rasul authored
* initial * initial * added initial convert script for paella vqmodel * initial wuerstchen pipeline * add LayerNorm2d * added modules * fix typo * use model_v2 * embed clip caption amd negative_caption * fixed name of var * initial modules in one place * WuerstchenPriorPipeline * inital shape * initial denoising prior loop * fix output * add WuerstchenPriorPipeline to __init__.py * use the noise ratio in the Prior * try to save pipeline * save_pretrained working * Few additions * add _execution_device * shape is int * fix batch size * fix shape of ratio * fix shape of ratio * fix output dataclass * tests folder * fix formatting * fix float16 + started with generator * Update pipeline_wuerstchen.py * removed vqgan code * add WuerstchenGeneratorPipeline * fix WuerstchenGeneratorPipeline * fix docstrings * fix imports * convert generator pipeline * fix convert * Work on Generator Pipeline. WIP * Pipeline works with our diffuzz code * apply scale factor * removed vqgan.py * use cosine schedule * redo the denoising loop * Update src/diffusers/models/resnet.py Co-authored-by:
Dominic Rampas <d6582533@gmail.com> Co-authored-by:
Dominic Rampas <61938694+dome272@users.noreply.github.com>
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- 05 Jul, 2023 1 commit
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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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- 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:
Sayak Paul <spsayakpaul@gmail.com> * changes based on review * add docs for paradigms * update docs with paradigms abstract * improve documentation, and add tests for ddim/ddpm batch_step_no_noise * fix docs and run make fix-copies * minor changes to docs. * Apply suggestions from code review Co-authored-by:
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- 16 May, 2023 1 commit
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clarencechen authored
* Add DPM-Solver Multistep Inverse Scheduler * Add draft tests for DiffEdit * Add inverse sde-dpmsolver steps to tune image diversity from inverted latents * Fix tests --------- Co-authored-by:
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- 27 Apr, 2023 1 commit
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Nipun Jindal authored
* [2064]: Add stochastic sampler * [2064]: Add stochastic sampler * [2064]: Add stochastic sampler * [2064]: Add stochastic sampler * [2064]: Add stochastic sampler * [2064]: Add stochastic sampler * [2064]: Add stochastic sampler * Review comments * [Review comment]: Add is_torchsde_available() * [Review comment]: Test and docs * [Review comment] * [Review comment] * [Review comment] * [Review comment] * [Review comment] --------- Co-authored-by:njindal <njindal@adobe.com>
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- 01 Mar, 2023 1 commit
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Patrick von Platen authored
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- 17 Feb, 2023 1 commit
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Patrick von Platen authored
* add * finish * add tests * add tests * up * up * pull from main * uP * Apply suggestions from code review * finish * Update docs/source/en/_toctree.yml Co-authored-by:
Suraj Patil <surajp815@gmail.com> * finish * clean docs * next * next * Apply suggestions from code review Co-authored-by:
Pedro Cuenca <pedro@huggingface.co> * up * up --------- Co-authored-by:
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- 16 Feb, 2023 1 commit
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Wenliang Zhao authored
* add UniPC scheduler * add the return type to the functions * code quality check * add tests * finish docs --------- Co-authored-by:
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- 17 Jan, 2023 1 commit
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Kashif Rasul authored
* added dit model * import * initial pipeline * initial convert script * initial pipeline * make style * raise valueerror * single function * rename classes * use DDIMScheduler * timesteps embedder * samples to cpu * fix var names * fix numpy type * use timesteps class for proj * fix typo * fix arg name * flip_sin_to_cos and better var names * fix C shape cal * make style * remove unused imports * cleanup * add back patch_size * initial dit doc * typo * Update docs/source/api/pipelines/dit.mdx Co-authored-by:
William Berman <WLBberman@gmail.com> Co-authored-by:
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- 04 Jan, 2023 1 commit
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qsh-zh authored
* feat : add log-rho deis multistep deis * docs :fix typo * docs : add docs for impl algo * docs : remove duplicate ref * finish deis * add docs * fix Co-authored-by:
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- 18 Dec, 2022 1 commit
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Will Berman authored
* [wip] attention block updates * [wip] unCLIP unet decoder and super res * [wip] unCLIP prior transformer * [wip] scheduler changes * [wip] text proj utility class * [wip] UnCLIPPipeline * [wip] kakaobrain unCLIP convert script * [unCLIP pipeline] fixes re: @patrickvonplaten remove callbacks move denoising loops into call function * UNCLIPScheduler re: @patrickvonplaten Revert changes to DDPMScheduler. Make UNCLIPScheduler, a modified DDPM scheduler with changes to support karlo * mask -> attention_mask re: @patrickvonplaten * [DDPMScheduler] remove leftover change * [docs] PriorTransformer * [docs] UNet2DConditionModel and UNet2DModel * [nit] UNCLIPScheduler -> UnCLIPScheduler matches existing unclip naming better * [docs] SchedulingUnCLIP * [docs] UnCLIPTextProjModel * refactor * finish licenses * rename all to attention_mask and prep in models * more renaming * don't expose unused configs * final renaming fixes * remove x attn mask when not necessary * configure kakao script to use new class embedding config * fix copies * [tests] UnCLIPScheduler * finish x attn * finish * remove more * rename condition blocks * clean more * Apply suggestions from code review * up * fix * [tests] UnCLIPPipelineFastTests * remove unused imports * [tests] UnCLIPPipelineIntegrationTests * correct * make style Co-authored-by:
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- 08 Dec, 2022 1 commit
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Anton Lozhkov authored
* Fix PyCharm/VSCode static type checking for dummy objects * Re-add dummies * Fix AudioDiffusion imports * fix import * fix import * Update utils/check_dummies.py Co-authored-by:
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- 07 Dec, 2022 1 commit
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Cheng Lu authored
* add singlestep dpmsolver * fix a style typo * fix a style typo * add docs * finish Co-authored-by:
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- 02 Dec, 2022 1 commit
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Patrick von Platen authored
* up * up * finish * finish * up * up * finish
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- 28 Nov, 2022 1 commit
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Patrick von Platen authored
* 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
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- 06 Nov, 2022 1 commit
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Cheng Lu authored
* add dpmsolver discrete pytorch scheduler * fix some typos in dpm-solver pytorch * add dpm-solver pytorch in stable-diffusion pipeline * add jax/flax version dpm-solver * change code style * change code style * add docs * add `add_noise` method for dpmsolver * add pytorch unit test for dpmsolver * add dummy object for pytorch dpmsolver * Update src/diffusers/schedulers/scheduling_dpmsolver_discrete.py Co-authored-by:
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- 03 Nov, 2022 2 commits
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Will Berman authored
* Changes for VQ-diffusion VQVAE Add specify dimension of embeddings to VQModel: `VQModel` will by default set the dimension of embeddings to the number of latent channels. The VQ-diffusion VQVAE has a smaller embedding dimension, 128, than number of latent channels, 256. Add AttnDownEncoderBlock2D and AttnUpDecoderBlock2D to the up and down unet block helpers. VQ-diffusion's VQVAE uses those two block types. * Changes for VQ-diffusion transformer Modify attention.py so SpatialTransformer can be used for VQ-diffusion's transformer. SpatialTransformer: - Can now operate over discrete inputs (classes of vector embeddings) as well as continuous. - `in_channels` was made optional in the constructor so two locations where it was passed as a positional arg were moved to kwargs - modified forward pass to take optional timestep embeddings ImagePositionalEmbeddings: - added to provide positional embeddings to discrete inputs for latent pixels BasicTransformerBlock: - norm layers were made configurable so that the VQ-diffusion could use AdaLayerNorm with timestep embeddings - modified forward pass to take optional timestep embeddings CrossAttention: - now may optionally take a bias parameter for its query, key, and value linear layers FeedForward: - Internal layers are now configurable ApproximateGELU: - Activation function in VQ-diffusion's feedforward layer AdaLayerNorm: - Norm layer modified to incorporate timestep embeddings * Add VQ-diffusion scheduler * Add VQ-diffusion pipeline * Add VQ-diffusion convert script to diffusers * Add VQ-diffusion dummy objects * Add VQ-diffusion markdown docs * Add VQ-diffusion tests * some renaming * some fixes * more renaming * correct * fix typo * correct weights * finalize * fix tests * Apply suggestions from code review Co-authored-by:
Anton Lozhkov <aglozhkov@gmail.com> * Apply suggestions from code review Co-authored-by:
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Revist authored
* feat: add repaint * fix: fix quality check with `make fix-copies` * fix: remove old unnecessary arg * chore: change default to DDPM (looks better in experiments) * ".to(device)" changed to "device=" Co-authored-by:
fja <fja@zurich.ibm.com> Co-authored-by:
Anton Lozhkov <anton@huggingface.co>
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- 31 Oct, 2022 1 commit
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hlky authored
* k-diffusion-euler * make style make quality * make fix-copies * fix tests for euler a * Update src/diffusers/schedulers/scheduling_euler_ancestral_discrete.py Co-authored-by:
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- 25 Oct, 2022 2 commits
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Patrick von Platen authored
* start * add more logic * Update src/diffusers/models/unet_2d_condition_flax.py * match weights * up * make model work * making class more general, fixing missed file rename * small fix * make new conversion work * up * finalize conversion * up * first batch of variable renamings * remove c and c_prev var names * add mid and out block structure * add pipeline * up * finish conversion * finish * upload * more fixes * Apply suggestions from code review * add attr * up * uP * up * finish tests * finish * uP * finish * fix test * up * naming consistency in tests * Apply suggestions from code review Co-authored-by:
Nathan Lambert <nathan@huggingface.co> Co-authored-by:
Nathan Lambert <nol@berkeley.edu> Co-authored-by:
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Kashif Rasul authored
* added broadcast_to_shape_from_left helper * initial tests * fixed pndm tests * shape required for pndm * added require_flax * fix style * fix more imports Co-authored-by:
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- 06 Oct, 2022 2 commits
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Anton Lozhkov authored
Temporarily remove Flax modules from the public API
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- 03 Oct, 2022 1 commit
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Pedro Cuenca authored
* 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)
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- 15 Sep, 2022 1 commit
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Kashif Rasul authored
* beta never changes removed from state * fix typos in docs * removed unused var * initial ddim flax scheduler * import * added dummy objects * fix style * fix typo * docs * fix typo in comment * set return type * added flax ddom * fix style * remake * pass PRNG key as argument and split before use * fix doc string * use config * added flax Karras VE scheduler * make style * fix dummy * fix ndarray type annotation * replace returns a new state * added lms_discrete scheduler * use self.config * add_noise needs state * use config * use config * docstring * added flax score sde ve * fix imports * fix typos
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- 13 Sep, 2022 1 commit
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Kashif Rasul authored
* initial flax pndm * fix typo * use state * return state * add FlaxSchedulerOutput * fix style * add flax imports * make style * fix typos * return created state * make style * add torch/flax imports * docs * fixed typo * remove tensor_format * round instead of cast * ets is jnp array * remove copy
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- 01 Sep, 2022 1 commit
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Anton Lozhkov authored
* Fix flake8 F401 '...' imported but unused * One more F403
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- 16 Aug, 2022 2 commits
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Patrick von Platen authored
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Anton Lozhkov authored
* test LMS with LDM * test LMS with LDM * Interchangeable sigma and timestep. Added dummy objects * Debug * cuda generator * Fix derivatives * Update tests * Rename Lms->LMS
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- 09 Aug, 2022 1 commit
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Anton Lozhkov authored
* karras + VE, not flexible yet * Fix inputs incompatibility with the original unet * Roll back sigma scaling * Apply suggestions from code review * Old comment * Fix doc
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- 13 Jul, 2022 1 commit
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Patrick von Platen authored
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- 27 Jun, 2022 1 commit
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Patrick von Platen authored
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- 26 Jun, 2022 1 commit
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Patrick von Platen authored
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- 25 Jun, 2022 2 commits
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Patrick von Platen authored
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Patrick von Platen authored
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- 21 Jun, 2022 1 commit
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anton-l authored
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- 16 Jun, 2022 2 commits
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patil-suraj authored
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patil-suraj authored
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