GitLab

* remove legacy code from load_attn_procs.

* finish first draft

* fix more.

* fix more

* add test

* add serialization support.

* fix-copies

* require peft backend for lora tests

* style

* fix test

* fix loading.

* empty

* address benjamin's feedback.

* use IPAdapterPlusImageProjectionBlock in IPAdapterPlusImageProjection

* reposition IPAdapterPlusImageProjection

* refactor complete?

* fix heads param retrieval.

* update test dict creation method.

* introduce _no_split_modules.

* unnecessary spaces.

* remove unnecessary kwargs and style

* fix: accelerate imports.

* change to _determine_device_map

* add the blocks that have residual connections.

* add: CrossAttnUpBlock2D

* add: testin

* style

* line-spaces

* quality

* add disk offload test without safetensors.

* checking disk offloading percentages.

* change model split

* add: utility for checking multi-gpu requirement.

* model parallelism test

* splits.

* splits.

* splits

* splits.

* splits.

* splits.

* offload folder to test_disk_offload_with_safetensors

* add _no_split_modules

* fix-copies

* Switch to peft and multi proj layers

* Move Face ID loading and inference to core

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

* reduce block sizes for unet1d.

* reduce blocks for unet_2d.

* reduce block size for unet_motion

* increase channels.

* correctly increase channels.

* reduce number of layers in unet2dconditionmodel tests.

* reduce block sizes for unet2dconditionmodel tests

* reduce block sizes for unet3dconditionmodel.

* fix: test_feed_forward_chunking

* fix: test_forward_with_norm_groups

* skip spatiotemporal tests on MPS.

* reduce block size in AutoencoderKL.

* reduce block sizes for vqmodel.

* further reduce block size.

* make style.

* Empty-Commit

* reduce sizes for ConsistencyDecoderVAETests

* further reduction.

* further block reductions in AutoencoderKL and AssymetricAutoencoderKL.

* massively reduce the block size in unet2dcontionmodel.

* reduce sizes for unet3d

* fix tests in unet3d.

* reduce blocks further in motion unet.

* fix: output shape

* add attention_head_dim to the test configuration.

* remove unexpected keyword arg

* up a bit.

* groups.

* up again

* fix

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

* begin IPAdapterTesterMixin



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

change to 2024

* harmonize the module structure for models in tests

* make the folders modules.

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

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

* refactor ip-adapter-imageproj, gligen

---------
Co-authored-by: yiyixuxu <yixu310@gmail,com>

update

* utils and test modifications to enable device agnostic testing

* device for manual seed in unet1d

* fix generator condition in vae test

* consistency changes to testing

* make style

* add device agnostic testing changes to source and one model test

* make dtype check fns private, log cuda fp16 case

* remove dtype checks from import utils, move to testing_utils

* adding tests for most model classes and one pipeline

* fix vae import

* Support IP-Adapter Plus

* fix format

* restore before black format

* restore before black format

* generic

* Refactor PerceiverAttention

* format

* fix test and refactor PerceiverAttention

* generic encode_image

* keep attention implementation

* merge tests

* encode_image backward compatible

* code quality

* fix controlnet inpaint pipeline

* refactor FFN

* refactor FFN

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

* add ip-adapter


---------
Co-authored-by: okotaku <to78314910@gmail.com>
Co-authored-by: sayakpaul <spsayakpaul@gmail.com>
Co-authored-by: yiyixuxu <yixu310@gmail,com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* Added args, kwargs to ```U

* Add UNetMidBlock2D as a supported mid block type

* Fix extra init input for UNetMidBlock2D, change allowed types for Mid-block init

* Update unet_2d_condition.py

* Update unet_2d_condition.py

* Update unet_2d_condition.py

* Update unet_2d_condition.py

* Update unet_2d_condition.py

* Update unet_2d_condition.py

* Update unet_2d_condition.py

* Update unet_2d_condition.py

* Update unet_2d_blocks.py

* Update unet_2d_blocks.py

* Update unet_2d_blocks.py

* Update unet_2d_condition.py

* Update unet_2d_blocks.py

* Updated docstring, increased check strictness

Updated the docstring for ```UNet2DConditionModel``` to include ```reverse_transformer_layers_per_block``` and updated checking for nested list type ```transformer_layers_per_block```

* Add basic shape-check test for asymmetrical unets

* Update src/diffusers/models/unet_2d_blocks.py

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

* Update unet_2d_condition.py

Remove blank space

* Update unet_2d_condition.py

Changed docstring for `mid_block_type`

* Fixed docstring and wrong default value

* Reformat with black

* Reformat with necessary commands

* Add UNetMidBlockFlat to versatile_diffusion/modeling_text_unet.py to ensure consistency

* Removed args, kwargs, use on mid-block type

* Make fix-copies

* Update src/diffusers/models/unet_2d_condition.py

Wrap into single line
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* make fix-copies

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

* fix other tests

* fix tests

* fix tests

* Update tests/pipelines/shap_e/test_shap_e_img2img.py

* Update tests/pipelines/shap_e/test_shap_e_img2img.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* fix upstream merge mistake

* fix tests:

* test fix

* Update tests/lora/test_lora_layers_old_backend.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update tests/lora/test_lora_layers_old_backend.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

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

* [LoRA] Centralize LoRA tests

* [LoRA] Centralize LoRA tests

* [LoRA] Centralize LoRA tests

* [LoRA] Centralize LoRA tests

* [LoRA] Centralize LoRA tests

* initial commit

* move modules to import struct

* add dummy objects and _LazyModule

* add lazy import to schedulers

* clean up unused imports

* lazy import on models module

* lazy import for schedulers module

* add lazy import to pipelines module

* lazy import altdiffusion

* lazy import audio diffusion

* lazy import audioldm

* lazy import consistency model

* lazy import controlnet

* lazy import dance diffusion ddim ddpm

* lazy import deepfloyd

* lazy import kandinksy

* lazy imports

* lazy import semantic diffusion

* lazy imports

* lazy import stable diffusion

* move sd output to its own module

* clean up

* lazy import t2iadapter

* lazy import unclip

* lazy import versatile and vq diffsuion

* lazy import vq diffusion

* helper to fetch objects from modules

* lazy import sdxl

* lazy import txt2vid

* lazy import stochastic karras

* fix model imports

* fix bug

* lazy import

* clean up

* clean up

* fixes for tests

* fixes for tests

* clean up

* remove import of torch_utils from utils module

* clean up

* clean up

* fix mistake import statement

* dedicated modules for exporting and loading

* remove testing utils from utils module

* fixes from  merge conflicts

* Update src/diffusers/pipelines/kandinsky2_2/__init__.py

* fix docs

* fix alt diffusion copied from

* fix check dummies

* fix more docs

* remove accelerate import from utils module

* add type checking

* make style

* fix check dummies

* remove torch import from xformers check

* clean up error message

* fixes after upstream merges

* dummy objects fix

* fix tests

* remove unused module import

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

* proposal for flaky tests

* more precision fixes

* move more tests to use cosine distance

* more test fixes

* clean up

* use default attn

* clean up

* update expected value

* make style

* make style

* Apply suggestions from code review

* Update src/diffusers/pipelines/stable_diffusion/pipeline_onnx_stable_diffusion_img2img.py

* make style

* fix failing tests

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

use max diff to compare model outputs

* make safetensors default

* set default save method as safetensors

* update tests

* update to support saving safetensors

* update test to account for safetensors default

* update example tests to use safetensors

* update example to support safetensors

* update unet tests for safetensors

* fix failing loader tests

* fix qc issues

* fix pipeline tests

* fix example test

---------
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* correct

* correct blocks

* finish

* finish

* finish

* Apply suggestions from code review

* fix

* up

* up

* up

* Update examples/dreambooth/README_sdxl.md
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Apply suggestions from code review

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

* add default to unet output to prevent it from being a required arg

* add unit test

* make style

* adjust unit test

* mark as fast test

* adjust assert statement in test

---------

Co-authored-by: Prathik Rao <prathikrao@microsoft.com@orttrainingdev8.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>
Co-authored-by: root <root@orttrainingdev8.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>

* relax tolerance slightly

* Add more tests

* upload readme

* upload readme

* Apply suggestions from code review

* Improve API Autoencoder KL

* finalize

* finalize tests

* finalize tests

* Apply suggestions from code review
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* up

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

* Cross-attention masks

prefer qualified symbol, fix accidental Optional

prefer qualified symbol in AttentionProcessor

prefer qualified symbol in embeddings.py

qualified symbol in transformed_2d

qualify FloatTensor in unet_2d_blocks

move new transformer_2d params attention_mask, encoder_attention_mask to the end of the section which is assumed (e.g. by functions such as checkpoint()) to have a stable positional param interface. regard return_dict as a special-case which is assumed to be injected separately from positional params (e.g. by create_custom_forward()).

move new encoder_attention_mask param to end of CrossAttn block interfaces and Unet2DCondition interface, to maintain positional param interface.

regenerate modeling_text_unet.py

remove unused import

unet_2d_condition encoder_attention_mask docs
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

versatile_diffusion/modeling_text_unet.py encoder_attention_mask docs
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

transformer_2d encoder_attention_mask docs
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

unet_2d_blocks.py: add parameter name comments
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

revert description. bool-to-bias treatment happens in unet_2d_condition only.

comment parameter names

fix copies, style

* encoder_attention_mask for SimpleCrossAttnDownBlock2D, SimpleCrossAttnUpBlock2D

* encoder_attention_mask for UNetMidBlock2DSimpleCrossAttn

* support attention_mask, encoder_attention_mask in KCrossAttnDownBlock2D, KCrossAttnUpBlock2D, KAttentionBlock. fix binding of attention_mask, cross_attention_kwargs params in KCrossAttnDownBlock2D, KCrossAttnUpBlock2D checkpoint invocations.

* fix mistake made during merge conflict resolution

* regenerate versatile_diffusion

* pass time embedding into checkpointed attention invocation

* always assume encoder_attention_mask is a mask (i.e. not a bias).

* style, fix-copies

* add tests for cross-attention masks

* add test for padding of attention mask

* explain mask's query_tokens dim. fix explanation about broadcasting over channels; we actually broadcast over query tokens

* support both masks and biases in Transformer2DModel#forward. document behaviour

* fix-copies

* delete attention_mask docs on the basis I never tested self-attention masking myself. not comfortable explaining it, since I don't actually understand how a self-attn mask can work in its current form: the key length will be different in every ResBlock (we don't downsample the mask when we downsample the image).

* review feedback: the standard Unet blocks shouldn't pass temb to attn (only to resnet). remove from KCrossAttnDownBlock2D,KCrossAttnUpBlock2D#forward.

* remove encoder_attention_mask param from SimpleCrossAttn{Up,Down}Block2D,UNetMidBlock2DSimpleCrossAttn, and mask-choice in those blocks' #forward, on the basis that they only do one type of attention, so the consumer can pass whichever type of attention_mask is appropriate.

* put attention mask padding back to how it was (since the SD use-case it enabled wasn't important, and it breaks the original unclip use-case). disable the test which was added.

* fix-copies

* style

* fix-copies

* put encoder_attention_mask param back into Simple block forward interfaces, to ensure consistency of forward interface.

* restore passing of emb to KAttentionBlock#forward, on the basis that removal caused test failures. restore also the passing of emb to checkpointed calls to KAttentionBlock#forward.

* make simple unet2d blocks use encoder_attention_mask, but only when attention_mask is None. this should fix UnCLIP compatibility.

* fix copies

* up

* fix more

* Apply suggestions from code review

* fix more

* fix more

* Check it

* Remove 16:8

* fix more

* fix more

* fix more

* up

* up

* Test only stable diffusion

* Test only two files

* up

* Try out spinning up processes that can be killed

* up

* Apply suggestions from code review

* up

* up

* enable deterministic pytorch and cuda operations.

* disable manual seeding.

* make style && make quality for unet_2d tests.

* enable determinism for the unet2dconditional model.

* add CUBLAS_WORKSPACE_CONFIG for better reproducibility.

* relax tolerance (very weird issue, though).

* revert to torch manual_seed() where needed.

* relax more tolerance.

* better placement of the cuda variable and relax more tolerance.

* enable determinism for 3d condition model.

* relax tolerance.

* add: determinism to alt_diffusion.

* relax tolerance for alt diffusion.

* dance diffusion.

* dance diffusion is flaky.

* test_dict_tuple_outputs_equivalent edit.

* fix two more tests.

* fix more ddim tests.

* fix: argument.

* change to diff in place of difference.

* fix: test_save_load call.

* test_save_load_float16 call.

* fix: expected_max_diff

* fix: paint by example.

* relax tolerance.

* add determinism to 1d unet model.

* torch 2.0 regressions seem to be brutal

* determinism to vae.

* add reason to skipping.

* up tolerance.

* determinism to vq.

* determinism to cuda.

* determinism to the generic test pipeline file.

* refactor general pipelines testing a bit.

* determinism to alt diffusion i2i

* up tolerance for alt diff i2i and audio diff

* up tolerance.

* determinism to audioldm

* increase tolerance for audioldm lms.

* increase tolerance for paint by paint.

* increase tolerance for repaint.

* determinism to cycle diffusion and sd 1.

* relax tol for cycle diffusion 🚲

* relax tol for sd 1.0

* relax tol for controlnet.

* determinism to img var.

* relax tol for img variation.

* tolerance to i2i sd

* make style

* determinism to inpaint.

* relax tolerance for inpaiting.

* determinism for inpainting legacy

* relax tolerance.

* determinism to instruct pix2pix

* determinism to model editing.

* model editing tolerance.

* panorama determinism

* determinism to pix2pix zero.

* determinism to sag.

* sd 2. determinism

* sd. tolerance

* disallow tf32 matmul.

* relax tolerance is all you need.

* make style and determinism to sd 2 depth

* relax tolerance for depth.

* tolerance to diffedit.

* tolerance to sd 2 inpaint.

* up tolerance.

* determinism in upscaling.

* tolerance in upscaler.

* more tolerance relaxation.

* determinism to v pred.

* up tol for v_pred

* unclip determinism

* determinism to unclip img2img

* determinism to text to video.

* determinism to last set of tests

* up tol.

* vq cumsum doesn't have a deterministic kernel

* relax tol

* relax tol

* diffusers==0.14.0 update

* custom diffusion update

* custom diffusion update

* custom diffusion update

* custom diffusion update

* custom diffusion update

* custom diffusion update

* custom diffusion

* custom diffusion

* custom diffusion

* custom diffusion

* custom diffusion

* apply formatting and get rid of bare except.

* refactor readme and other minor changes.

* misc refactor.

* fix: repo_id issue and loaders logging bug.

* fix: save_model_card.

* fix: save_model_card.

* fix: save_model_card.

* add: doc entry.

* refactor doc,.

* custom diffusion

* custom diffusion

* custom diffusion

* apply style.

* remove tralining whitespace.

* fix: toctree entry.

* remove unnecessary print.

* custom diffusion

* custom diffusion

* custom diffusion test

* custom diffusion xformer update

* custom diffusion xformer update

* custom diffusion xformer update

---------
Co-authored-by: Nupur Kumari <nupurkumari@Nupurs-MacBook-Pro.local>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Nupur Kumari <nupurkumari@nupurs-mbp.wifi.local.cmu.edu>

* [Tests] parallelize

* finish folder structuring

* Parallelize tests more

* Correct saving of pipelines

* make sure logging level is correct

* try again

* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

---------
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* inital commit for lora test cases

* help a bit with lora for 3d

* fixed lora tests

* replaced redundant code

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

* Helper function to disable custom attention processors.

* Restore code deleted by mistake.

* Format

* Fix modeling_text_unet copy.

* Add AudioLDM

* up

* add vocoder

* start unet

* unconditional unet

* clap, vocoder and vae

* clean-up: conversion scripts

* fix: conversion script token_type_ids

* clean-up: pipeline docstring

* tests: from SD

* clean-up: cpu offload vocoder instead of safety checker

* feat: adapt tests to audioldm

* feat: add docs

* clean-up: amend pipeline docstrings

* clean-up: make style

* clean-up: make fix-copies

* fix: add doc path to toctree

* clean-up: args for conversion script

* clean-up: paths to checkpoints

* fix: use conditional unet

* clean-up: make style

* fix: type hints for UNet

* clean-up: docstring for UNet

* clean-up: make style

* clean-up: remove duplicate in docstring

* clean-up: make style

* clean-up: make fix-copies

* clean-up: move imports to start in code snippet

* fix: pass cross_attention_dim as a list/tuple to unet

* clean-up: make fix-copies

* fix: update checkpoint path

* fix: unet cross_attention_dim in tests

* film embeddings -> class embeddings

* Apply suggestions from code review
Co-authored-by: Will Berman <wlbberman@gmail.com>

* fix: unet film embed to use existing args

* fix: unet tests to use existing args

* fix: make style

* fix: transformers import and version in init

* clean-up: make style

* Revert "clean-up: make style"

This reverts commit 5d6d1f8b324f5583e7805dc01e2c86e493660d66.

* clean-up: make style

* clean-up: use pipeline tester mixin tests where poss

* clean-up: skip attn slicing test

* fix: add torch dtype to docs

* fix: remove conversion script out of src

* fix: remove .detach from 1d waveform

* fix: reduce default num inf steps

* fix: swap height/width -> audio_length_in_s

* clean-up: make style

* fix: remove nightly tests

* fix: imports in conversion script

* clean-up: slim-down to two slow tests

* clean-up: slim-down fast tests

* fix: batch consistent tests

* clean-up: make style

* clean-up: remove vae slicing fast test

* clean-up: propagate changes to doc

* fix: increase test tol to 1e-2

* clean-up: finish docs

* clean-up: make style

* feat: vocoder / VAE compatibility check

* feat: possibly expand / cut audio waveform

* fix: pipeline call signature test

* fix: slow tests output len

* clean-up: make style

* make style

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

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

* Adding `use_safetensors` argument to give more control to users

about which weights they use.

* Doc style.

* Rebased (not functional).

* Rebased and functional with tests.

* Style.

* Apply suggestions from code review

* Style.

* Addressing comments.

* Update tests/test_pipelines.py
Co-authored-by: Will Berman <wlbberman@gmail.com>

* Black ???

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

* rename file

* rename attention

* fix more

* rename more

* up

* more deprecation imports

* fixes

* fix AttnProcessor2_0

Fix use of AttnProcessor2_0 for cross attention with mask

* added scale_qk and out_bias flags

* fixed for xformers

* check if it has scale argument

* Update cross_attention.py

* check torch version

* fix sliced attn

* style

* set scale

* fix test

* fixed addedKV processor

* revert back AttnProcessor2_0

* if missing if

* fix inner_dim

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

* Fix regression introduced in #2448

* Style.

* Adding support for `safetensors` and LoRa.

* Adding metadata.