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  1. 05 Aug, 2025 1 commit
  3. 17 Jul, 2025 1 commit
  5. 19 Jun, 2025 1 commit
  7. 11 Jun, 2025 1 commit
  9. 07 May, 2025 1 commit
    • Aryan's avatar
      Cosmos (#10660) · 7b904941
      Aryan authored 
      

* begin transformer conversion

* refactor

* refactor

* refactor

* refactor

* refactor

* refactor

* update

* add conversion script

* add pipeline

* make fix-copies

* remove einops

* update docs

* gradient checkpointing

* add transformer test

* update

* debug

* remove prints

* match sigmas

* add vae pt. 1

* finish CV* vae

* update

* update

* update

* update

* update

* update

* make fix-copies

* update

* make fix-copies

* fix

* update

* update

* make fix-copies

* update

* update tests

* handle device and dtype for safety checker; required in latest diffusers

* remove enable_gqa and use repeat_interleave instead

* enforce safety checker; use dummy checker in fast tests

* add review suggestion for ONNX export
Co-Authored-By: default avatarAsfiya Baig <asfiyab@nvidia.com>

* fix safety_checker issues when not passed explicitly

We could either do what's done in this commit, or update the Cosmos examples to explicitly pass the safety checker

* use cosmos guardrail package

* auto format docs

* update conversion script to support 14B models

* update name CosmosPipeline -> CosmosTextToWorldPipeline

* update docs

* fix docs

* fix group offload test failing for vae

---------
Co-authored-by: default avatarAsfiya Baig <asfiyab@nvidia.com>
      7b904941
  11. 01 May, 2025 1 commit
  13. 30 Apr, 2025 1 commit
  15. 21 Apr, 2025 1 commit
  17. 10 Apr, 2025 1 commit
  19. 02 Apr, 2025 1 commit
  21. 12 Mar, 2025 1 commit
  23. 11 Mar, 2025 1 commit
  25. 10 Mar, 2025 1 commit
  27. 21 Feb, 2025 1 commit
  29. 23 Jan, 2025 1 commit
  31. 14 Jan, 2025 1 commit
    • Marc Sun's avatar
      [FEAT] DDUF format (#10037) · fbff43ac
      Marc Sun authored 
      

* load and save dduf archive

* style

* switch to zip uncompressed

* updates

* Update src/diffusers/pipelines/pipeline_utils.py
Co-authored-by: default avatarSayak Paul <spsayakpaul@gmail.com>

* Update src/diffusers/pipelines/pipeline_utils.py
Co-authored-by: default avatarSayak Paul <spsayakpaul@gmail.com>

* first draft

* remove print

* switch to dduf_file for consistency

* switch to huggingface hub api

* fix log

* add a basic test

* Update src/diffusers/configuration_utils.py
Co-authored-by: default avatarSayak Paul <spsayakpaul@gmail.com>

* Update src/diffusers/pipelines/pipeline_utils.py
Co-authored-by: default avatarSayak Paul <spsayakpaul@gmail.com>

* Update src/diffusers/pipelines/pipeline_utils.py
Co-authored-by: default avatarSayak Paul <spsayakpaul@gmail.com>

* fix

* fix variant

* change saving logic

* DDUF - Load transformers components manually (#10171)

* update hfh version

* Load transformers components manually

* load encoder from_pretrained with state_dict

* working version with transformers and tokenizer !

* add generation_config case

* fix tests

* remove saving for now

* typing

* need next version from transformers

* Update src/diffusers/configuration_utils.py
Co-authored-by: default avatarLucain <lucain@huggingface.co>

* check path corectly

* Apply suggestions from code review
Co-authored-by: default avatarLucain <lucain@huggingface.co>

* udapte

* typing

* remove check for subfolder

* quality

* revert setup changes

* oups

* more readable condition

* add loading from the hub test

* add basic docs.

* Apply suggestions from code review
Co-authored-by: default avatarLucain <lucain@huggingface.co>

* add example

* add

* make functions private

* Apply suggestions from code review
Co-authored-by: default avatarSteven Liu <59462357+stevhliu@users.noreply.github.com>

* minor.

* fixes

* fix

* change the precdence of parameterized.

* error out when custom pipeline is passed with dduf_file.

* updates

* fix

* updates

* fixes

* updates

* fix xfail condition.

* fix xfail

* fixes

* sharded checkpoint compat

* add test for sharded checkpoint

* add suggestions

* Update src/diffusers/models/model_loading_utils.py
Co-authored-by: default avatarYiYi Xu <yixu310@gmail.com>

* from suggestions

* add class attributes to flag dduf tests

* last one

* fix logic

* remove comment

* revert changes

---------
Co-authored-by: default avatarSayak Paul <spsayakpaul@gmail.com>
Co-authored-by: default avatarLucain <lucain@huggingface.co>
Co-authored-by: default avatarSteven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: default avatarYiYi Xu <yixu310@gmail.com>
      fbff43ac
  33. 17 Dec, 2024 1 commit
  35. 16 Dec, 2024 1 commit
  37. 06 Dec, 2024 1 commit
  39. 21 Oct, 2024 1 commit
    • Sayak Paul's avatar
      [Quantization] Add quantization support for `bitsandbytes` (#9213) · b821f006
      Sayak Paul authored 
      * quantization config.

* fix-copies

* fix

* modules_to_not_convert

* add bitsandbytes utilities.

* make progress.

* fixes

* quality

* up

* up

rotary embedding refactor 2: update comments, fix dtype for use_real=False (#9312)

fix notes and dtype

up

up

* minor

* up

* up

* fix

* provide credits where due.

* make configurations work.

* fixes

* fix

* update_missing_keys

* fix

* fix

* make it work.

* fix

* provide credits to transformers.

* empty commit

* handle to() better.

* tests

* change to bnb from bitsandbytes

* fix tests

fix slow quality tests

SD3 remark

fix

complete int4 tests

add a readme to the test files.

add model cpu offload tests

warning test

* better safeguard.

* change merging status

* courtesy to transformers.

* move  upper.

* better

* make the unused kwargs warning friendlier.

* harmonize changes with https://github.com/huggingface/transformers/pull/33122



* style

* trainin tests

* feedback part i.

* Add Flux inpainting and Flux Img2Img (#9135)

---------
Co-authored-by: default avataryiyixuxu <yixu310@gmail.com>

Update `UNet2DConditionModel`'s error messages (#9230)

* refactor

[CI] Update Single file Nightly Tests (#9357)

* update

* update

feedback.

improve README for flux dreambooth lora (#9290)

* improve readme

* improve readme

* improve readme

* improve readme

fix one uncaught deprecation warning for accessing vae_latent_channels in VaeImagePreprocessor (#9372)

deprecation warning vae_latent_channels

add mixed int8 tests and more tests to nf4.

[core] Freenoise memory improvements (#9262)

* update

* implement prompt interpolation

* make style

* resnet memory optimizations

* more memory optimizations; todo: refactor

* update

* update animatediff controlnet with latest changes

* refactor chunked inference changes

* remove print statements

* update

* chunk -> split

* remove changes from incorrect conflict resolution

* remove changes from incorrect conflict resolution

* add explanation of SplitInferenceModule

* update docs

* Revert "update docs"

This reverts commit c55a50a271b2cefa8fe340a4f2a3ab9b9d374ec0.

* update docstring for freenoise split inference

* apply suggestions from review

* add tests

* apply suggestions from review

quantization docs.

docs.

* Revert "Add Flux inpainting and Flux Img2Img (#9135)"

This reverts commit 5799954dd4b3d753c7c1b8d722941350fe4f62ca.

* tests

* don

* Apply suggestions from code review
Co-authored-by: default avatarSteven Liu <59462357+stevhliu@users.noreply.github.com>

* contribution guide.

* changes

* empty

* fix tests

* harmonize with https://github.com/huggingface/transformers/pull/33546

.

* numpy_cosine_distance

* config_dict modification.

* remove if config comment.

* note for load_state_dict changes.

* float8 check.

* quantizer.

* raise an error for non-True low_cpu_mem_usage values when using quant.

* low_cpu_mem_usage shenanigans when using fp32 modules.

* don't re-assign _pre_quantization_type.

* make comments clear.

* remove comments.

* handle mixed types better when moving to cpu.

* add tests to check if we're throwing warning rightly.

* better check.

* fix 8bit test_quality.

* handle dtype more robustly.

* better message when keep_in_fp32_modules.

* handle dtype casting.

* fix dtype checks in pipeline.

* fix warning message.

* Update src/diffusers/models/modeling_utils.py
Co-authored-by: default avatarYiYi Xu <yixu310@gmail.com>

* mitigate the confusing cpu warning

---------
Co-authored-by: default avatarVishnu V Jaddipal <95531133+Gothos@users.noreply.github.com>
Co-authored-by: default avatarSteven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: default avatarYiYi Xu <yixu310@gmail.com>
      b821f006
  41. 07 Oct, 2024 1 commit
  43. 12 Aug, 2024 1 commit
  45. 05 Aug, 2024 1 commit
  47. 23 Jul, 2024 1 commit
    • Tolga Cangöz's avatar
      Fix Colab and Notebook checks for `diffusers-cli env` (#8408) · cf55dcf0
      Tolga Cangöz authored 
      

* chore: Update is_google_colab check to use environment variable

* Check Colab with all possible COLAB_* env variables

* Remove unnecessary word

* Make `_is_google_colab` more inclusive

* Revert "Make `_is_google_colab` more inclusive"

This reverts commit 6406db21ac46139c20ccae20ccb44877eec87ba7.

* Make `_is_google_colab` more inclusive.

* chore: Update import_utils.py with notebook check improvement

* Refactor import_utils.py to improve notebook detection for VS Code's notebook

* chore: Remove `is_notebook()` function and related code

---------
Co-authored-by: default avatarSayak Paul <spsayakpaul@gmail.com>
      cf55dcf0
  49. 07 Jun, 2024 1 commit
    • Sayak Paul's avatar
      [Core] support saving and loading of sharded checkpoints (#7830) · 7d887118
      Sayak Paul authored 
      

* feat: support saving a model in sharded checkpoints.

* feat: make loading of sharded checkpoints work.

* add tests

* cleanse the loading logic a bit more.

* more resilience while loading from the Hub.

* parallelize shard downloads by using snapshot_download()/

* default to a shard size.

* more fix

* Empty-Commit

* debug

* fix

* uality

* more debugging

* fix more

* initial comments from Benjamin

* move certain methods to loading_utils

* add test to check if the correct number of shards are present.

* add a test to check if loading of sharded checkpoints from the Hub is okay

* clarify the unit when passed as an int.

* use hf_hub for sharding.

* remove unnecessary code

* remove unnecessary function

* lucain's comments.

* fixes

* address high-level comments.

* fix test

* subfolder shenanigans./

* Update src/diffusers/utils/hub_utils.py
Co-authored-by: default avatarLucain <lucainp@gmail.com>

* Apply suggestions from code review
Co-authored-by: default avatarLucain <lucainp@gmail.com>

* remove _huggingface_hub_version as not needed.

* address more feedback.

* add a test for local_files_only=True/

* need hf hub to be at least 0.23.2

* style

* final comment.

* clean up subfolder.

* deal with suffixes in code.

* _add_variant default.

* use weights_name_pattern

* remove add_suffix_keyword

* clean up downloading of sharded ckpts.

* don't return something special when using index.json

* fix more

* don't use bare except

* remove comments and catch the errors better

* fix a couple of things when using is_file()

* empty

---------
Co-authored-by: default avatarLucain <lucainp@gmail.com>
      7d887118
  51. 27 May, 2024 1 commit
    • Anton Obukhov's avatar
      [Pipeline] Marigold depth and normals estimation (#7847) · b3d10d6d
      Anton Obukhov authored 
      

* implement marigold depth and normals pipelines in diffusers core

* remove bibtex

* remove deprecations

* remove save_memory argument

* remove validate_vae

* remove config output

* remove batch_size autodetection

* remove presets logic
move default denoising_steps and processing_resolution into the model config
make default ensemble_size 1

* remove no_grad

* add fp16 to the example usage

* implement is_matplotlib_available
use is_matplotlib_available, is_scipy_available for conditional imports in the marigold depth pipeline

* move colormap, visualize_depth, and visualize_normals into export_utils.py

* make the denoising loop more lucid
fix the outputs to always be 4d tensors or lists of pil images
support a 4d input_image case
attempt to support model_cpu_offload_seq
move check_inputs into a separate function
change default batch_size to 1, remove any logic to make it bigger implicitly

* style

* rename denoising_steps into num_inference_steps

* rename input_image into image

* rename input_latent into latents

* remove decode_image
change decode_prediction to use the AutoencoderKL.decode method

* move clean_latent outside of progress_bar

* refactor marigold-reusable image processing bits into MarigoldImageProcessor class

* clean up the usage example docstring

* make ensemble functions members of the pipelines

* add early checks in check_inputs
rename E into ensemble_size in depth ensembling

* fix vae_scale_factor computation

* better compatibility with torch.compile
better variable naming

* move export_depth_to_png to export_utils

* remove encode_prediction

* improve visualize_depth and visualize_normals to accept multi-dimensional data and lists
remove visualization functions from the pipelines
move exporting depth as 16-bit PNGs functionality from the depth pipeline
update example docstrings

* do not shortcut vae.config variables

* change all asserts to raise ValueError

* rename output_prediction_type to output_type

* better variable names
clean up variable deletion code

* better variable names

* pass desc and leave kwargs into the diffusers progress_bar
implement nested progress bar for images and steps loops

* implement scale_invariant and shift_invariant flags in the ensemble_depth function
add scale_invariant and shift_invariant flags readout from the model config
further refactor ensemble_depth
support ensembling without alignment
add ensemble_depth docstring

* fix generator device placement checks

* move encode_empty_text body into the pipeline call

* minor empty text encoding simplifications

* adjust pipelines' class docstrings to explain the added construction arguments

* improve the scipy failure condition
add comments
improve docstrings
change the default use_full_z_range to True

* make input image values range check configurable in the preprocessor
refactor load_image_canonical in preprocessor to reject unknown types and return the image in the expected 4D format of tensor and on right device
support a list of everything as inputs to the pipeline, change type to PipelineImageInput
implement a check that all input list elements have the same dimensions
improve docstrings of pipeline outputs
remove check_input pipeline argument

* remove forgotten print

* add prediction_type model config

* add uncertainty visualization into export utils
fix NaN values in normals uncertainties

* change default of output_uncertainty to False
better handle the case of an attempt to export or visualize none

* fix `output_uncertainty=False`

* remove kwargs
fix check_inputs according to the new inputs of the pipeline

* rename prepare_latent into prepare_latents as in other pipelines
annotate prepare_latents in normals pipeline with "Copied from"
annotate encode_image in normals pipeline with "Copied from"

* move nested-capable `progress_bar` method into the pipelines
revert the original `progress_bar` method in pipeline_utils

* minor message improvement

* fix cpu offloading

* move colormap, visualize_depth, export_depth_to_16bit_png, visualize_normals, visualize_uncertainty to marigold_image_processing.py
update example docstrings

* fix missing comma

* change torch.FloatTensor to torch.Tensor

* fix importing of MarigoldImageProcessor

* fix vae offloading
fix batched image encoding
remove separate encode_image function and use vae.encode instead

* implement marigold's intial tests
relax generator checks in line with other pipelines
implement return_dict __call__ argument in line with other pipelines

* fix num_images computation

* remove MarigoldImageProcessor and outputs from import structure
update tests

* update docstrings

* update init

* update

* style

* fix

* fix

* up

* up

* up

* add simple test

* up

* update expected np input/output to be channel last

* move expand_tensor_or_array into the MarigoldImageProcessor

* rewrite tests to follow conventions - hardcoded slices instead of image artifacts
write more smoke tests

* add basic docs.

* add anton's contribution statement

* remove todos.

* fix assertion values for marigold depth slow tests

* fix assertion values for depth normals.

* remove print

* support AutoencoderTiny in the pipelines

* update documentation page
add Available Pipelines section
add Available Checkpoints section
add warning about num_inference_steps

* fix missing import in docstring
fix wrong value in visualize_depth docstring

* [doc] add marigold to pipelines overview

* [doc] add section "usage examples"

* fix an issue with latents check in the pipelines

* add "Frame-by-frame Video Processing with Consistency" section

* grammarly

* replace tables with images with css-styled images (blindly)

* style

* print

* fix the assertions.

* take from the github runner.

* take the slices from action artifacts

* style.

* update with the slices from the runner.

* remove unnecessary code blocks.

* Revert "[doc] add marigold to pipelines overview"

This reverts commit a505165150afd8dab23c474d1a054ea505a56a5f.

* remove invitation for new modalities

* split out marigold usage examples

* doc cleanup

---------
Co-authored-by: default avataryiyixuxu <yixu310@gmail.com>
Co-authored-by: default avataryiyixuxu <yixu310@gmail,com>
Co-authored-by: default avatarsayakpaul <spsayakpaul@gmail.com>
      b3d10d6d
  53. 15 May, 2024 1 commit
    • Isamu Isozaki's avatar
      Adding VQGAN Training script (#5483) · d27e996c
      Isamu Isozaki authored 
      

* Init commit

* Removed einops

* Added default movq config for training

* Update explanation of prompts

* Fixed inheritance of discriminator and init_tracker

* Fixed incompatible api between muse and here

* Fixed output

* Setup init training

* Basic structure done

* Removed attention for quick tests

* Style fixes

* Fixed vae/vqgan styles

* Removed redefinition of wandb

* Fixed log_validation and tqdm

* Nothing commit

* Added commit loss to lookup_from_codebook

* Update src/diffusers/models/vq_model.py
Co-authored-by: default avatarSayak Paul <spsayakpaul@gmail.com>

* Adding perliminary README

* Fixed one typo

* Local changes

* Fixed main issues

* Merging

* Update src/diffusers/models/vq_model.py
Co-authored-by: default avatarSayak Paul <spsayakpaul@gmail.com>

* Testing+Fixed bugs in training script

* Some style fixes

* Added wandb to docs

* Fixed timm test

* get testing suite ready.

* remove return loss

* remove return_loss

* Remove diffs

* Remove diffs

* fix ruff format

---------
Co-authored-by: default avatarSayak Paul <spsayakpaul@gmail.com>
Co-authored-by: default avatarDhruv Nair <dhruv.nair@gmail.com>
      d27e996c
  55. 14 May, 2024 1 commit
    • Tolga Cangöz's avatar
      Expansion proposal of `diffusers-cli env` (#7403) · a1245c2c
      Tolga Cangöz authored 
      

* Expand `diffusers-cli env`

* SafeTensors -> Safetensors
Co-authored-by: default avatarSayak Paul <spsayakpaul@gmail.com>

* Move `safetensors_version = "not installed"` to `else`

* Update `safetensors_version` checking

* Add GPU detection for Linux, Mac OS, and Windows

* Add accelerator detection to environment command

* Add is_peft_version to import_utils

* Update env.py

* Add `huggingface_hub` reference

* Add `transformers` reference

* Add reference for `huggingface_hub`

* Fix print statement in env.py for unusual OS

* Up

* Fix platform information in env.py

* up

* Fix import order in env.py

* ruff

* make style

* Fix platform system check in env.py

* Fix run method return type in env.py

* 🤗



* No need f-string

* Remove location info

* Remove accelerate config

* Refactor env.py to remove accelerate config

* feat: Add support for `bitsandbytes` library in environment command

---------
Co-authored-by: default avatarSayak Paul <spsayakpaul@gmail.com>
Co-authored-by: default avatarDhruv Nair <dhruv.nair@gmail.com>
      a1245c2c
  57. 26 Mar, 2024 1 commit
    • Sayak Paul's avatar
      feat: support DoRA LoRA from community (#7371) · 699dfb08
      Sayak Paul authored 
      * feat: support dora loras from community

* safe-guard dora operations under peft version.

* pop use_dora when False

* make dora lora from kohya work.

* fix: kohya conversion utils.

* add a fast test for DoRA compatibility..

* add a nightly test.
      699dfb08
  59. 09 Mar, 2024 1 commit
  61. 08 Feb, 2024 1 commit
  63. 01 Feb, 2024 1 commit
  65. 15 Jan, 2024 1 commit
    • Sayak Paul's avatar
      [OmegaConf] replace it with `yaml` (#6488) · cb4b3f0b
      Sayak Paul authored 
      * remove omegaconf from convert_from_ckpt.

* remove from single_file.

* change to string based ubscription.

* style

* okay

* fix: vae_param

* no . indexing.

* style

* style

* turn getattrs into explicit if/else

* style

* propagate changes to ldm_uncond.

* propagate to gligen

* propagate to if.

* fix: quotes.

* propagate to audioldm.

* propagate to audioldm2

* propagate to musicldm.

* propagate to vq_diffusion

* propagate to zero123.

* remove omegaconf from diffusers codebase.
      cb4b3f0b
  67. 11 Oct, 2023 1 commit
  69. 25 Sep, 2023 1 commit
  71. 22 Sep, 2023 1 commit
  73. 11 Sep, 2023 2 commits
    • Patrick von Platen's avatar
      [Core] Remove TF import checks (#4968) · 2c60f7d1
      Patrick von Platen authored 
      [TF] Remove tf
      2c60f7d1
    • 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
  75. 22 Aug, 2023 1 commit
  77. 11 Aug, 2023 1 commit