"src/vscode:/vscode.git/clone" did not exist on "f1cb807496ab456c52b48574171aaa83902fab6d"
  1. 08 Feb, 2024 1 commit
  2. 22 Jan, 2024 1 commit
  3. 21 Dec, 2023 1 commit
    • Will Berman's avatar
      open muse (#5437) · 40398152
      Will Berman authored
      
      
      amused
      
      rename
      
      Update docs/source/en/api/pipelines/amused.md
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      AdaLayerNormContinuous default values
      
      custom micro conditioning
      
      micro conditioning docs
      
      put lookup from codebook in constructor
      
      fix conversion script
      
      remove manual fused flash attn kernel
      
      add training script
      
      temp remove training script
      
      add dummy gradient checkpointing func
      
      clarify temperatures is an instance variable by setting it
      
      remove additional SkipFF block args
      
      hardcode norm args
      
      rename tests folder
      
      fix paths and samples
      
      fix tests
      
      add training script
      
      training readme
      
      lora saving and loading
      
      non-lora saving/loading
      
      some readme fixes
      
      guards
      
      Update docs/source/en/api/pipelines/amused.md
      Co-authored-by: default avatarSuraj Patil <surajp815@gmail.com>
      
      Update examples/amused/README.md
      Co-authored-by: default avatarSuraj Patil <surajp815@gmail.com>
      
      Update examples/amused/train_amused.py
      Co-authored-by: default avatarSuraj Patil <surajp815@gmail.com>
      
      vae upcasting
      
      add fp16 integration tests
      
      use tuple for micro cond
      
      copyrights
      
      remove casts
      
      delegate to torch.nn.LayerNorm
      
      move temperature to pipeline call
      
      upsampling/downsampling changes
      40398152
  4. 27 Nov, 2023 1 commit
  5. 09 Nov, 2023 1 commit
  6. 24 Oct, 2023 1 commit
    • dg845's avatar
      Add Latent Consistency Models Pipeline (#5448) · 958e17da
      dg845 authored
      
      
      * initial commit for LatentConsistencyModelPipeline and LCMScheduler based on the community pipeline
      
      * Add callback and freeu support.
      
      * apply suggestions from review
      
      * Clean up LCMScheduler
      
      * Remove timeindex argument to LCMScheduler.step.
      
      * Add support for clipping or thresholding the predicted original sample.
      
      * Remove unused methods and arguments in LCMScheduler.
      
      * Improve comment about (lack of) negative prompt support.
      
      * Change input guidance_scale to match the StableDiffusionPipeline (Imagen) CFG formulation.
      
      * Move lcm_origin_steps from pipeline __call__ to LCMScheduler.__init__/config (as origin_steps).
      
      * Fix typo when clipping/thresholding in LCMScheduler.
      
      * Add some initial LCMScheduler tests.
      
      * add type annotations from review
      
      * Fix type annotation bug.
      
      * Override test_add_noise_device in LCMSchedulerTest since hardcoded timesteps doesn't work under default settings.
      
      * Add generator argument pipeline prepare_latents call.
      
      * Cast LCMScheduler.timesteps to long in set_timesteps.
      
      * Add onestep and multistep full loop scheduler tests.
      
      * Set default height/width to None and don't hardcode guidance scale embedding dim.
      
      * Add initial LatentConsistencyPipeline fast and slow tests.
      
      * Add initial documentation for LatentConsistencyModelPipeline and LCMScheduler.
      
      * Make remaining failing fast tests pass.
      
      * make style
      
      * Make original_inference_steps configurable from pipeline __call__ again.
      
      * make style
      
      * Remove guidance_rescale arg from pipeline __call__ since LCM currently doesn't support CFG.
      
      * Make LCMScheduler defaults match config of LCM_Dreamshaper_v7 checkpoint.
      
      * Fix LatentConsistencyPipeline slow tests and add dummy expected slices.
      
      * Add checks for original_steps in LCMScheduler.set_timesteps.
      
      * make fix-copies
      
      * Improve LatentConsistencyModelPipeline docs.
      
      * Apply suggestions from code review
      Co-authored-by: default avatarAryan V S <avs050602@gmail.com>
      
      * Apply suggestions from code review
      Co-authored-by: default avatarAryan V S <avs050602@gmail.com>
      
      * Apply suggestions from code review
      Co-authored-by: default avatarAryan V S <avs050602@gmail.com>
      
      * Update src/diffusers/schedulers/scheduling_lcm.py
      
      * Apply suggestions from code review
      Co-authored-by: default avatarAryan V S <avs050602@gmail.com>
      
      * finish
      
      ---------
      Co-authored-by: default avatarSayak Paul <spsayakpaul@gmail.com>
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      Co-authored-by: default avatarAryan V S <avs050602@gmail.com>
      958e17da
  7. 25 Sep, 2023 1 commit
  8. 22 Sep, 2023 1 commit
    • Pedro Cuenca's avatar
      SDXL flax (#4254) · 3651b14c
      Pedro Cuenca authored
      
      
      * support transformer_layers_per block in flax UNet
      
      * add support for text_time additional embeddings to Flax UNet
      
      * rename attention layers for VAE
      
      * add shape asserts when renaming attention layers
      
      * transpose VAE attention layers
      
      * add pipeline flax SDXL code [WIP]
      
      * continue add pipeline flax SDXL code [WIP]
      
      * cleanup
      
      * Working on JIT support
      
      Fixed prompt embedding shapes so they work in parallel mode. Assuming we
      always have both text encoders for now, for simplicity.
      
      * Fixing embeddings (untested)
      
      * Remove spurious line
      
      * Shard guidance_scale when jitting.
      
      * Decode images
      
      * Fix sharding
      
      * style
      
      * Refiner UNet can be loaded.
      
      * Refiner / img2img pipeline
      
      * Allow latent outputs from base and latent inputs in refiner
      
      This makes it possible to chain base + refiner without having to use the
      vae decoder in the base model, the vae encoder in the refiner, skipping
      conversions to/from PIL, and avoiding TPU <-> CPU memory copies.
      
      * Adapt to FlaxCLIPTextModelOutput
      
      * Update Flax XL pipeline to FlaxCLIPTextModelOutput
      
      * make fix-copies
      
      * make style
      
      * add euler scheduler
      
      * Fix import
      
      * Fix copies, comment unused code.
      
      * Fix SDXL Flax imports
      
      * Fix euler discrete begin
      
      * improve init import
      
      * finish
      
      * put discrete euler in init
      
      * fix flax euler
      
      * Fix more
      
      * make style
      
      * correct init
      
      * correct init
      
      * Temporarily remove FlaxStableDiffusionXLImg2ImgPipeline
      
      * correct pipelines
      
      * finish
      
      ---------
      Co-authored-by: default avatarMartin Müller <martin.muller.me@gmail.com>
      Co-authored-by: default avatarpatil-suraj <surajp815@gmail.com>
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      3651b14c
  9. 12 Sep, 2023 1 commit
  10. 11 Sep, 2023 1 commit
    • Dhruv Nair's avatar
      Lazy Import for Diffusers (#4829) · b6e0b016
      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: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      b6e0b016
  11. 06 Sep, 2023 1 commit
    • Kashif Rasul's avatar
      Würstchen model (#3849) · 541bb6ee
      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: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * use torch.lerp
      
      * use warp-diffusion org
      
      * clip_sample=False,
      
      * some refactoring
      
      * use model_v3_stage_c
      
      * c_cond size
      
      * use clip-bigG
      
      * allow stage b clip to be None
      
      * add dummy
      
      * würstchen scheduler
      
      * minor changes
      
      * set clip=None in the pipeline
      
      * fix attention mask
      
      * add attention_masks to text_encoder
      
      * make fix-copies
      
      * add back clip
      
      * add text_encoder
      
      * gen_text_encoder and tokenizer
      
      * fix import
      
      * updated pipeline test
      
      * undo changes to pipeline test
      
      * nip
      
      * fix typo
      
      * fix output name
      
      * set guidance_scale=0 and remove diffuze
      
      * fix doc strings
      
      * make style
      
      * nip
      
      * removed unused
      
      * initial docs
      
      * rename
      
      * toc
      
      * cleanup
      
      * remvoe test script
      
      * fix-copies
      
      * fix multi images
      
      * remove dup
      
      * remove unused modules
      
      * undo changes for debugging
      
      * no  new line
      
      * remove dup conversion script
      
      * fix doc string
      
      * cleanup
      
      * pass default args
      
      * dup permute
      
      * fix some tests
      
      * fix prepare_latents
      
      * move Prior class to modules
      
      * offload only the text encoder and vqgan
      
      * fix resolution calculation for prior
      
      * nip
      
      * removed testing script
      
      * fix shape
      
      * fix argument to set_timesteps
      
      * do not change .gitignore
      
      * fix resolution calculations + readme
      
      * resolution calculation fix + readme
      
      * small fixes
      
      * Add combined pipeline
      
      * rename generator -> decoder
      
      * Update .gitignore
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * removed efficient_net
      
      * create combined WuerstchenPipeline
      
      * make arguments consistent with VQ model
      
      * fix var names
      
      * no need to return text_encoder_hidden_states
      
      * add latent_dim_scale to config
      
      * split model into its own file
      
      * add WuerschenPipeline to docs
      
      * remove unused latent_size
      
      * register latent_dim_scale
      
      * update script
      
      * update docstring
      
      * use Attention preprocessor
      
      * concat with normed input
      
      * fix-copies
      
      * add docs
      
      * fix test
      
      * fix style
      
      * add to cpu_offloaded_model
      
      * updated type
      
      * remove 1-line func
      
      * updated type
      
      * initial decoder test
      
      * formatting
      
      * formatting
      
      * fix autodoc link
      
      * num_inference_steps is int
      
      * remove comments
      
      * fix example in docs
      
      * Update src/diffusers/pipelines/wuerstchen/diffnext.py
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * rename layernorm to WuerstchenLayerNorm
      
      * rename DiffNext to WuerstchenDiffNeXt
      
      * added comment about MixingResidualBlock
      
      * move paella vq-vae to pipelines' folder
      
      * initial decoder test
      
      * increased test_float16_inference expected diff
      
      * self_attn is always true
      
      * more passing decoder tests
      
      * batch image_embeds
      
      * fix failing tests
      
      * set the correct dtype
      
      * relax inference test
      
      * update prior
      
      * added combined pipeline test
      
      * faster test
      
      * faster test
      
      * Update src/diffusers/pipelines/wuerstchen/pipeline_wuerstchen_combined.py
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * fix issues from review
      
      * update wuerstchen.md + change generator name
      
      * resolve issues
      
      * fix copied from usage and add back batch_size
      
      * fix API
      
      * fix arguments
      
      * fix combined test
      
      * Added timesteps argument + fixes
      
      * Update tests/pipelines/test_pipelines_common.py
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * Update tests/pipelines/wuerstchen/test_wuerstchen_prior.py
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * Update src/diffusers/pipelines/wuerstchen/pipeline_wuerstchen_combined.py
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * Update src/diffusers/pipelines/wuerstchen/pipeline_wuerstchen_combined.py
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * Update src/diffusers/pipelines/wuerstchen/pipeline_wuerstchen_combined.py
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * Update src/diffusers/pipelines/wuerstchen/pipeline_wuerstchen_combined.py
      
      * up
      
      * Fix more
      
      * failing tests
      
      * up
      
      * up
      
      * correct naming
      
      * correct docs
      
      * correct docs
      
      * fix test params
      
      * correct docs
      
      * fix classifier free guidance
      
      * fix classifier free guidance
      
      * fix more
      
      * fix all
      
      * make tests faster
      
      ---------
      Co-authored-by: default avatarDominic Rampas <d6582533@gmail.com>
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      Co-authored-by: default avatarDominic Rampas <61938694+dome272@users.noreply.github.com>
      541bb6ee
  12. 05 Jul, 2023 1 commit
    • dg845's avatar
      Add Consistency Models Pipeline (#3492) · aed7499a
      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: default avatarayushmangal <ayushmangal@microsoft.com>
      Co-authored-by: default avatarAyush Mangal <43698245+ayushtues@users.noreply.github.com>
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      aed7499a
  13. 20 Jun, 2023 1 commit
  14. 16 May, 2023 1 commit
  15. 27 Apr, 2023 1 commit
    • Nipun Jindal's avatar
      [2064]: Add stochastic sampler (sample_dpmpp_sde) (#3020) · fd512d74
      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: default avatarnjindal <njindal@adobe.com>
      fd512d74
  16. 01 Mar, 2023 1 commit
  17. 17 Feb, 2023 1 commit
  18. 16 Feb, 2023 1 commit
  19. 17 Jan, 2023 1 commit
    • Kashif Rasul's avatar
      DiT Pipeline (#1806) · 37d113cc
      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: default avatarSuraj Patil <surajp815@gmail.com>
      
      * added copyright license headers
      
      * added example usage and toc
      
      * fix variable names asserts
      
      * remove comment
      
      * added docs
      
      * fix typo
      
      * upstream changes
      
      * set proper device for drop_ids
      
      * added initial dit pipeline test
      
      * update docs
      
      * fix imports
      
      * make fix-copies
      
      * isort
      
      * fix imports
      
      * get rid of more magic numbers
      
      * fix code when guidance is off
      
      * remove block_kwargs
      
      * cleanup script
      
      * removed to_2tuple
      
      * use FeedForward class instead of another MLP
      
      * style
      
      * work on mergint DiTBlock with BasicTransformerBlock
      
      * added missing final_dropout and args to BasicTransformerBlock
      
      * use norm from block
      
      * fix arg
      
      * remove unused arg
      
      * fix call to class_embedder
      
      * use timesteps
      
      * make style
      
      * attn_output gets multiplied
      
      * removed commented code
      
      * use Transformer2D
      
      * use self.is_input_patches
      
      * fix flags
      
      * fixed conversion to use Transformer2DModel
      
      * fixes for pipeline
      
      * remove dit.py
      
      * fix timesteps device
      
      * use randn_tensor and fix fp16 inf.
      
      * timesteps_emb already the right dtype
      
      * fix dit test class
      
      * fix test and style
      
      * fix norm2 usage in vq-diffusion
      
      * added author names to pipeline and lmagenet labels link
      
      * fix tests
      
      * use norm_type as string
      
      * rename dit to transformer
      
      * fix name
      
      * fix test
      
      * set  norm_type = "layer" by default
      
      * fix tests
      
      * do not skip common tests
      
      * Update src/diffusers/models/attention.py
      Co-authored-by: default avatarSuraj Patil <surajp815@gmail.com>
      
      * revert AdaLayerNorm API
      
      * fix norm_type name
      
      * make sure all components are in eval mode
      
      * revert norm2 API
      
      * compact
      
      * finish deprecation
      
      * add slow tests
      
      * remove @
      
      * refactor some stuff
      
      * upload
      
      * Update src/diffusers/pipelines/dit/pipeline_dit.py
      
      * finish more
      
      * finish docs
      
      * improve docs
      
      * finish docs
      Co-authored-by: default avatarSuraj Patil <surajp815@gmail.com>
      Co-authored-by: default avatarWilliam Berman <WLBberman@gmail.com>
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      37d113cc
  20. 04 Jan, 2023 1 commit
  21. 18 Dec, 2022 1 commit
    • Will Berman's avatar
      kakaobrain unCLIP (#1428) · 2dcf64b7
      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: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      2dcf64b7
  22. 08 Dec, 2022 1 commit
  23. 07 Dec, 2022 1 commit
  24. 02 Dec, 2022 1 commit
  25. 28 Nov, 2022 1 commit
    • Patrick von Platen's avatar
      Add 2nd order heun scheduler (#1336) · 4c54519e
      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
      4c54519e
  26. 06 Nov, 2022 1 commit
    • Cheng Lu's avatar
      Add multistep DPM-Solver discrete scheduler (#1132) · b4a1ed85
      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: default avatarSuraj Patil <surajp815@gmail.com>
      
      * Update tests/test_config.py
      Co-authored-by: default avatarSuraj Patil <surajp815@gmail.com>
      
      * Update tests/test_config.py
      Co-authored-by: default avatarSuraj Patil <surajp815@gmail.com>
      
      * resolve the code comments
      
      * rename the file
      
      * change class name
      
      * fix code style
      
      * add auto docs for dpmsolver multistep
      
      * add more explanations for the stabilizing trick (for steps < 15)
      
      * delete the dummy file
      
      * change the API name of predict_epsilon, algorithm_type and solver_type
      
      * add compatible lists
      Co-authored-by: default avatarSuraj Patil <surajp815@gmail.com>
      b4a1ed85
  27. 03 Nov, 2022 2 commits
    • Will Berman's avatar
      VQ-diffusion (#658) · ef2ea33c
      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: default avatarAnton Lozhkov <aglozhkov@gmail.com>
      
      * Apply suggestions from code review
      Co-authored-by: default avatarPedro Cuenca <pedro@huggingface.co>
      
      * finish
      
      * finish
      
      * up
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      Co-authored-by: default avatarAnton Lozhkov <aglozhkov@gmail.com>
      Co-authored-by: default avatarPedro Cuenca <pedro@huggingface.co>
      ef2ea33c
    • Revist's avatar
      feat: add repaint (#974) · d38c8043
      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: default avatarAnton Lozhkov <aglozhkov@gmail.com>
      
      * make generator device-specific
      Co-authored-by: default avatarAnton Lozhkov <aglozhkov@gmail.com>
      
      * make generator device-specific and change shape
      Co-authored-by: default avatarAnton Lozhkov <aglozhkov@gmail.com>
      
      * fix: add preprocessing for image and mask
      Co-authored-by: default avatarAnton Lozhkov <aglozhkov@gmail.com>
      
      * fix: update test
      Co-authored-by: default avatarAnton Lozhkov <aglozhkov@gmail.com>
      
      * Update src/diffusers/pipelines/repaint/pipeline_repaint.py
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * Add docs and examples
      
      * Fix toctree
      Co-authored-by: default avatarfja <fja@zurich.ibm.com>
      Co-authored-by: default avatarAnton Lozhkov <aglozhkov@gmail.com>
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      Co-authored-by: default avatarAnton Lozhkov <anton@huggingface.co>
      d38c8043
  28. 31 Oct, 2022 1 commit
  29. 25 Oct, 2022 2 commits
  30. 06 Oct, 2022 2 commits
  31. 03 Oct, 2022 1 commit
    • Pedro Cuenca's avatar
      Fix import with Flax but without PyTorch (#688) · 688031c5
      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)
      688031c5
  32. 15 Sep, 2022 1 commit
    • Kashif Rasul's avatar
      Karras VE, DDIM and DDPM flax schedulers (#508) · b34be039
      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
      b34be039
  33. 13 Sep, 2022 1 commit
    • Kashif Rasul's avatar
      initial flax pndm schedular (#492) · 55f7ca3b
      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
      55f7ca3b
  34. 01 Sep, 2022 1 commit
  35. 16 Aug, 2022 2 commits
  36. 09 Aug, 2022 1 commit