GitLab

docs: Update Imagen Video paper link in scheduler docstrings.

* refactor: enhance type hints and documentation in EulerDiscreteScheduler

Updated type hints for function parameters and return types in the EulerDiscreteScheduler class to improve code clarity and maintainability. Enhanced docstrings for several methods to provide clearer descriptions of their functionality and expected arguments. This includes specifying Literal types for certain parameters and ensuring consistent return type annotations across the class.

* refactor: enhance type hints and documentation across multiple schedulers

Updated type hints and improved docstrings in various scheduler classes, including CMStochasticIterativeScheduler, CosineDPMSolverMultistepScheduler, and others. This includes specifying parameter types, return types, and providing clearer descriptions of method functionalities. Notable changes include the addition of default values in the begin_index argument and enhanced explanations for noise addition methods. These improvements aim to enhance code clarity and maintainability across the scheduling module.

* refactor: update docstrings to clarify noise schedule construction

Revised docstrings across multiple scheduler classes to enhance clarity regarding the construction of noise schedules. Updated references to relevant papers, ensuring accurate citations for the methodologies used. This includes changes in DEISMultistepScheduler, DPMSolverMultistepInverseScheduler, and others, improving documentation consistency and readability.

update

* Use HF Papers

* Apply style fixes

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* 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: Asfiya 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

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Co-authored-by: Asfiya Baig <asfiyab@nvidia.com>

* Slight performance improvement to Euler

* Slight performance improvement to EDMEuler

* Slight performance improvement to FlowMatchHeun

* Slight performance improvement to KDPM2Ancestral

* Update KDPM2AncestralDiscreteSchedulerTest

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Co-authored-by: YiYi Xu <yixu310@gmail.com>

Co-authored-by: YiYi Xu <yixu310@gmail.com>

* fix: euledm when using the exp sigma schedule.

* fix-copies

* remove print.

* reduce friction

* yiyi's suggestioms

* Merged isinstance calls to make the code simpler.

* Corrected formatting errors using ruff.

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* find & replace all FloatTensors to Tensor

* apply formatting

* Update torch.FloatTensor to torch.Tensor in the remaining files

* formatting

* Fix the rest of the places where FloatTensor is used as well as in documentation

* formatting

* Update new file from FloatTensor to Tensor

* introduce sigma schedule.
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* address yiyi

* update docstrings.

* implement the schedule for EDMDPMSolverMultistepScheduler

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Co-authored-by: Suraj Patil <surajp815@gmail.com>

* add: utility to format our docs too 📜

* debugging saga

* fix: message

* checking

* should be fixed.

* revert pipeline_fixture

* remove empty line

* make style

* fix: setup.py

* style.

* Fix typos

* Fix typo in SVD.md

* fix

* fix

* add a tests

* fix

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: yiyixuxu <yixu310@gmail,com>

* 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

* Add EDMEulerScheduler

* address review comments

* fix import

* fix test

* add tests

* add co-author

Co-authored-by:  @dg845 dgu8957@gmail.com

change to 2024

* 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.

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* correct

* Apply suggestions from code review

* make style

* ruff format

* not need to use doc-builder's black styling as the doc is styled in ruff

* make fix-copies

* comment

* use run_ruff

* 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

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Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

add self.step_index

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Co-authored-by: yiyixuxu <yixu310@gmail,com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* clean scheduler mixin

* up to dpmsolvermultistep

* finish cleaning

* first draft

* fix overview table

* apply feedback

* update reference code

* 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: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/pipelines/shap_e/pipeline_shap_e.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/pipelines/shap_e/pipeline_shap_e.py
Co-authored-by: Patrick 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: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/models/prior_transformer.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/models/prior_transformer.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/models/prior_transformer.py

add arg: encoder_hid_proj
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/models/prior_transformer.py

add new config: norm_in_type
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/models/prior_transformer.py

add new config: added_emb_type
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/models/prior_transformer.py

rename out_dim -> clip_embed_dim
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/models/prior_transformer.py

rename config: out_dim -> clip_embed_dim
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/models/prior_transformer.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/models/prior_transformer.py
Co-authored-by: Patrick 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: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/pipelines/shap_e/pipeline_shap_e_img2img.py
Co-authored-by: Patrick 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: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Patrick 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: yiyixuxu <yixu310@gmail,com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* 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: Patrick 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: Patrick von Platen <patrick.v.platen@gmail.com>

* 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: Suraj 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: Suraj 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: Suraj Patil <surajp815@gmail.com>
Co-authored-by: William Berman <WLBberman@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* [Repro] Correct reproducability

* up

* up

* uP

* up

* need better image

* allow conversion from no state dict checkpoints

* up

* up

* up

* up

* check tensors

* check tensors

* check tensors

* check tensors

* next try

* up

* up

* better name

* up

* up

* Apply suggestions from code review

* correct more

* up

* replace all torch randn

* fix

* correct

* correct

* finish

* fix more

* up

* up

* up

* finish

* finish

* up

* up

* finish

* support v prediction in other schedulers

* v heun

* add tests for v pred

* fix tests

* fix test euler a

* v ddpm

* 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