1. 09 May, 2024 1 commit
  2. 03 Apr, 2024 2 commits
    • Beinsezii's avatar
      UniPC Multistep add `rescale_betas_zero_snr` (#7531) · aa190259
      Beinsezii authored
      * UniPC Multistep add `rescale_betas_zero_snr`
      
      Same patch as DPM and Euler with the patched final alpha cumprod
      
      BF16 doesn't seem to break down, I think cause UniPC upcasts during some
      phases already? We could still force an upcast since it only
      loses ≈ 0.005 it/s for me but the difference in output is very small. A
      better endeavor might upcasting in step() and removing all the other
      upcasts elsewhere?
      
      * UniPC ZSNR UT
      
      * Re-add `rescale_betas_zsnr` doc oops
      aa190259
    • Beinsezii's avatar
      UniPC Multistep fix tensor dtype/device on order=3 (#7532) · 19ab04ff
      Beinsezii authored
      * UniPC UTs iterate solvers on FP16
      
      It wasn't catching errs on order==3. Might be excessive?
      
      * UniPC Multistep fix tensor dtype/device on order=3
      
      * UniPC UTs Add v_pred to fp16 test iter
      
      For completions sake. Probably overkill?
      19ab04ff
  3. 30 Mar, 2024 1 commit
    • Beinsezii's avatar
      Add `final_sigma_zero` to UniPCMultistep (#7517) · f0c81562
      Beinsezii authored
      * Add `final_sigma_zero` to UniPCMultistep
      
      Effectively the same trick as DDIM's `set_alpha_to_one` and
      DPM's `final_sigma_type='zero'`.
      Currently False by default but maybe this should be True?
      
      * `final_sigma_zero: bool` -> `final_sigmas_type: str`
      
      Should 1:1 match DPM Multistep now.
      
      * Set `final_sigmas_type='sigma_min'` in UniPC UTs
      f0c81562
  4. 19 Mar, 2024 1 commit
  5. 18 Mar, 2024 1 commit
    • M. Tolga Cangöz's avatar
      Fix Typos (#7325) · 6a05b274
      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
      6a05b274
  6. 05 Mar, 2024 1 commit
  7. 27 Feb, 2024 3 commits
  8. 11 Feb, 2024 1 commit
  9. 08 Feb, 2024 1 commit
  10. 22 Jan, 2024 1 commit
  11. 19 Jan, 2024 1 commit
  12. 26 Dec, 2023 2 commits
  13. 20 Dec, 2023 1 commit
    • Beinsezii's avatar
      EulerAncestral add `rescale_betas_zero_snr` (#6187) · 457abdf2
      Beinsezii authored
      
      
      * EulerAncestral add `rescale_betas_zero_snr`
      
      Uses same infinite sigma fix from EulerDiscrete. Interestingly the
      ancestral version had the opposite problem: too much contrast instead of
      too little.
      
      * UT for EulerAncestral `rescale_betas_zero_snr`
      
      * EulerAncestral upcast samples during step()
      
      It helps this scheduler too, particularly when the model is using bf16.
      
      While the noise dtype is still the model's it's automatically upcasted
      for the add so all it affects is determinism.
      
      ---------
      Co-authored-by: default avatarSayak Paul <spsayakpaul@gmail.com>
      457abdf2
  14. 07 Dec, 2023 1 commit
  15. 29 Nov, 2023 1 commit
    • Suraj Patil's avatar
      Add SVD (#5895) · 63f767ef
      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: default avatarPatrick 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: default avatarDhruv Nair <dhruv.nair@gmail.com>
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      Co-authored-by: default avatarapolinário <joaopaulo.passos@gmail.com>
      63f767ef
  16. 27 Nov, 2023 1 commit
    • dg845's avatar
      Add Custom Timesteps Support to LCMScheduler and Supported Pipelines (#5874) · 67d07074
      dg845 authored
      * Add custom timesteps support to LCMScheduler.
      
      * Add custom timesteps support to StableDiffusionPipeline.
      
      * Add custom timesteps support to StableDiffusionXLPipeline.
      
      * Add custom timesteps support to remaining Stable Diffusion pipelines which support LCMScheduler (img2img, inpaint).
      
      * Add custom timesteps support to remaining Stable Diffusion XL pipelines which support LCMScheduler (img2img, inpaint).
      
      * Add custom timesteps support to StableDiffusionControlNetPipeline.
      
      * Add custom timesteps support to T21 Stable Diffusion (XL) Adapters.
      
      * Clean up Stable Diffusion inpaint tests.
      
      * Manually add support for custom timesteps to AltDiffusion pipelines since make fix-copies doesn't appear to work correctly (it deletes the whole pipeline).
      
      * make style
      
      * Refactor pipeline timestep handling into the retrieve_timesteps function.
      67d07074
  17. 20 Nov, 2023 1 commit
  18. 07 Nov, 2023 1 commit
    • dg845's avatar
      Improve LCMScheduler (#5681) · aab6de22
      dg845 authored
      
      
      * Refactor LCMScheduler.step such that prev_sample == denoised at the last timestep in the schedule.
      
      * Make timestep scaling when calculating boundary conditions configurable.
      
      * Reparameterize timestep_scaling to be a multiplicative rather than division scaling.
      
      * make style
      
      * fix dtype conversion
      
      * make style
      
      ---------
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      aab6de22
  19. 30 Oct, 2023 1 commit
  20. 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
  21. 02 Oct, 2023 1 commit
  22. 29 Sep, 2023 2 commits
  23. 27 Sep, 2023 1 commit
  24. 19 Sep, 2023 1 commit
  25. 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
  26. 23 Aug, 2023 1 commit
  27. 16 Aug, 2023 1 commit
  28. 15 Aug, 2023 1 commit
  29. 18 Jul, 2023 1 commit
    • clarencechen's avatar
      Add Recent Timestep Scheduling Improvements to DDIM Inverse Scheduler (#3865) · c6e56e92
      clarencechen authored
      * Add Recent Timestep Scheduling Improvements to DDIM Inverse Scheduler
      
      Roll timesteps by one to reflect origin-destination semantic discrepancy
      
      Restore `set_alpha_to_one` option to handle negative initial timesteps
      
      Remove `set_alpha_to_zero` option not used due to previous truncation
      
      * Bugfix
      
      * Remove unnecessary calls to `detach()`
      
      Use `self.image_processor.preprocess` in DiffEdit pipeline functions
      
      * Preprocess list input for inverted image latents in diffedit pipeline
      
      * Add `timestep_spacing` and `steps_offset` to `DPMSolverMultistepInverseScheduler`
      
      * Update expected test results to account for inverting last forward diffusion step
      
      * Fix inversion progress bar bug
      
      * Add first draft for proper fast tests for DDIMInverseScheduler
      
      * Add deprecated DDIMInverseScheduler kwarg to ConfigMixer registry
      
      * Fix test failure in DPMMultistepInverseScheduler
      
      Invert step specification leads to negative noise variance in SDE-based algs
      
      Add first draft for proper fast tests for DPMMultistepInverseScheduler
      
      * Update expected test results to account for inverting last forward diffusion step
      
      Clean up diffedit fast test
      c6e56e92
  30. 06 Jul, 2023 1 commit
    • YiYi Xu's avatar
      Add Shap-E (#3742) · 45f6d52b
      YiYi Xu authored
      
      
      * refactor prior_transformer
      
      adding conversion script
      
      add pipeline
      
      add step_index from pipeline, + remove permute
      
      add zero pad token
      
      remove copy from statement for betas_for_alpha_bar function
      
      * add
      
      * add
      
      * update conversion script for renderer model
      
      * refactor camera a little bit
      
      * clean up
      
      * style
      
      * fix copies
      
      * Update src/diffusers/schedulers/scheduling_heun_discrete.py
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * Update src/diffusers/pipelines/shap_e/pipeline_shap_e.py
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * Update src/diffusers/pipelines/shap_e/pipeline_shap_e.py
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * alpha_transform_type
      
      * remove step_index argument
      
      * remove get_sigmas_karras
      
      * remove _yiyi_sigma_to_t
      
      * move the rescale prompt_embeds from prior_transformer to pipeline
      
      * replace baddbmm with einsum to match origial repo
      
      * Revert "replace baddbmm with einsum to match origial repo"
      
      This reverts commit 3f6b435d65dad3e5514cad2f5dd9e4419ca78e0b.
      
      * add step_index to scale_model_input
      
      * Revert "move the rescale prompt_embeds from prior_transformer to pipeline"
      
      This reverts commit 5b5a8e6be918fefd114a2945ed89d8e8fa8be21b.
      
      * move rescale from prior_transformer to pipeline
      
      * correct step_index in scale_model_input
      
      * remove print lines
      
      * refactor prior - reduce arguments
      
      * make style
      
      * add prior_image
      
      * arg embedding_proj_norm -> norm_embedding_proj
      
      * add pre-norm for proj_embedding
      
      * move rescale prompt from pipeline to _encode_prompt
      
      * add img2img pipeline
      
      * style
      
      * copies
      
      * Update src/diffusers/models/prior_transformer.py
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * Update src/diffusers/models/prior_transformer.py
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * Update src/diffusers/models/prior_transformer.py
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * Update src/diffusers/models/prior_transformer.py
      
      add arg: encoder_hid_proj
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * Update src/diffusers/models/prior_transformer.py
      
      add new config: norm_in_type
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * Update src/diffusers/models/prior_transformer.py
      
      add new config: added_emb_type
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * Update src/diffusers/models/prior_transformer.py
      
      rename out_dim -> clip_embed_dim
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * Update src/diffusers/models/prior_transformer.py
      
      rename config: out_dim -> clip_embed_dim
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * Update src/diffusers/models/prior_transformer.py
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * Update src/diffusers/models/prior_transformer.py
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * finish refactor prior_tranformer
      
      * make style
      
      * refactor renderer
      
      * fix
      
      * make style
      
      * refactor img2img
      
      * remove params_proj
      
      * add test
      
      * add upcast_softmax to prior_transformer
      
      * enable num_images_per_prompt, add save_gif utility
      
      * add
      
      * add fast test
      
      * make style
      
      * add slow test
      
      * style
      
      * add test for img2img
      
      * refactor
      
      * enable batching
      
      * style
      
      * refactor scheduler
      
      * update test
      
      * style
      
      * attempt to solve batch related tests timeout
      
      * add doc
      
      * Update src/diffusers/pipelines/shap_e/pipeline_shap_e.py
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * Update src/diffusers/pipelines/shap_e/pipeline_shap_e_img2img.py
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * hardcode rendering related config
      
      * update betas_for_alpha_bar on ddpm_scheduler
      
      * fix copies
      
      * fix
      
      * export_to_gif
      
      * style
      
      * second attempt to speed up batching tests
      
      * add doc page to index
      
      * Remove intermediate clipping
      
      * 3rd attempt to speed up batching tests
      
      * Remvoe time index
      
      * simplify scheduler
      
      * Fix more
      
      * Fix more
      
      * fix more
      
      * make style
      
      * fix schedulers
      
      * fix some more tests
      
      * finish
      
      * add one more test
      
      * Apply suggestions from code review
      Co-authored-by: default avatarSayak Paul <spsayakpaul@gmail.com>
      Co-authored-by: default avatarPedro Cuenca <pedro@huggingface.co>
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * style
      
      * apply feedbacks
      
      * style
      
      * fix copies
      
      * add one example
      
      * style
      
      * add example for img2img
      
      * fix doc
      
      * fix more doc strings
      
      * size -> frame_size
      
      * style
      
      * update doc
      
      * style
      
      * fix on doc
      
      * update repo name
      
      * improve the usage example in shap-e img2img
      
      * add usage examples in the shap-e docs.
      
      * consolidate examples.
      
      * minor fix.
      
      * update doc
      
      * Apply suggestions from code review
      
      * Apply suggestions from code review
      
      * remove upcast
      
      * Make sure background is white
      
      * Update src/diffusers/pipelines/shap_e/pipeline_shap_e.py
      
      * Apply suggestions from code review
      
      * Finish
      
      * Apply suggestions from code review
      
      * Update src/diffusers/pipelines/shap_e/pipeline_shap_e.py
      
      * Make style
      
      ---------
      Co-authored-by: default avataryiyixuxu <yixu310@gmail,com>
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      Co-authored-by: default avatarSayak Paul <spsayakpaul@gmail.com>
      Co-authored-by: default avatarPedro Cuenca <pedro@huggingface.co>
      45f6d52b
  31. 05 Jul, 2023 2 commits
    • 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
    • Pedro Cuenca's avatar
      Add `timestep_spacing` and `steps_offset` to schedulers (#3947) · 07c9a08e
      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: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * Missing args in DPMSolverMultistep
      
      * Test: default args not in config
      
      * Style
      
      * Fix scheduler name in test
      
      * Remove duplicated entries
      
      * Add test for solver_type
      
      This test currently fails in main. When switching from DEIS to UniPC,
      solver_type is "logrho" (the default value from DEIS), which gets
      translated to "bh1" by UniPC. This is different to the default value for
      UniPC: "bh2". This is where the translation happens: https://github.com/huggingface/diffusers/blob/36d22d0709dc19776e3016fb3392d0f5578b0ab2/src/diffusers/schedulers/scheduling_unipc_multistep.py#L171
      
      
      
      * UniPC: use same default for solver_type
      
      Fixes a bug when switching from UniPC from another scheduler (i.e.,
      DEIS) that uses a different solver type. The solver is now the same as
      if we had instantiated the scheduler directly.
      
      * do not save use default values
      
      * fix more
      
      * fix all
      
      * fix schedulers
      
      * fix more
      
      * finish for real
      
      * finish for real
      
      * flaky tests
      
      * Update tests/pipelines/stable_diffusion/test_stable_diffusion_pix2pix_zero.py
      
      * Default steps_offset to 0.
      
      * Add missing docstrings
      
      * Apply suggestions from code review
      
      ---------
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      07c9a08e
  32. 20 Jun, 2023 1 commit
  33. 07 Jun, 2023 1 commit
  34. 22 May, 2023 1 commit