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94 Commits

Author SHA1 Message Date
Dhruv Nair
57afaff270 update 2024-02-13 03:47:00 +00:00
Dhruv Nair
e7b2032082 update 2024-02-12 18:22:36 +00:00
Dhruv Nair
2d5e9c2e39 update 2024-02-12 16:10:28 +00:00
Dhruv Nair
d68635f950 update 2024-02-12 14:24:24 +00:00
Sayak Paul
371f765908 [Diffusers -> Original SD conversion] fix things (#6933)
* fix: bias loading bug

* fixes for SDXL

* apply changes to the conversion script to match single_file_utils.py

* do transpose to match the single file loading logic.
2024-02-12 17:30:22 +05:30
Piyush Thakur
75aee39eac [Model Card] standardize T2I Adapter Sdxl model card (#6947)
standardize model card template t21-adapter-sdxl
2024-02-12 16:43:20 +05:30
Dhruv Nair
215e6804d3 Unpin torch versions in CI (#6945)
* update

* update

* update

---------

Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
2024-02-12 16:01:05 +05:30
Disty0
9254d1f39a Pass device to enable_model_cpu_offload in maybe_free_model_hooks (#6937) 2024-02-12 13:42:32 +05:30
Piyush Thakur
e1bdcc7af3 [Model Card] standardize T2I Sdxl Lora model card (#6944)
* standardize model card template t2i-lora-sdxl

* type annotations
2024-02-12 11:45:40 +05:30
Dhruv Nair
84905ca728 Update PixArt Alpha test module to match src module (#6943)
update
2024-02-12 11:01:33 +05:30
Piyush Thakur
6f336650c3 [Model Card] standardize T2I Sdxl model card (#6942)
standardize model card template t2i-sdxl
2024-02-12 10:01:20 +05:30
Piyush Thakur
06a042cd0e [Model Card] standardize T2I Lora model card (#6940)
standardize model card t2i-lora
2024-02-12 10:01:13 +05:30
Piyush Thakur
8772496586 [Model Card] standardize T2I model card (#6939)
* standardize model card

* fix base_model
2024-02-12 10:00:41 +05:30
dg845
35fd84be27 Replace hardcoded values in SchedulerCommonTest with properties (#5479)
---------

Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
2024-02-10 21:34:20 -10:00
YiYi Xu
f2756253e6 Fix a bug in AutoPipeline.from_pipe when switching pipeline with optional components (#6820)
* fix

* add tests

---------

Co-authored-by: yiyixuxu <yixu310@gmail,com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
2024-02-09 21:56:52 -10:00
YiYi Xu
0071478d9e allow attention processors to have different signatures (#6915)
add

Co-authored-by: yiyixuxu <yixu310@gmail,com>
2024-02-09 21:56:19 -10:00
Sayak Paul
7c8cab313e post release 0.26.2 (#6885)
* post release

* style

* Empty-Commit

---------

Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
2024-02-09 07:36:38 -10:00
Sayak Paul
ca9ed5e8d1 [LoRA] deprecate certain lora methods from the old backend. (#6889)
* deprecate certain lora methods from the old backend.

* uncomment necessary things.

* safe remove old lora backend 👋
2024-02-09 17:14:32 +01:00
Bingxin Ke
98b6bee1a1 [Community Pipeline][Bug Fix] marigold_depth_estimation: input image value range (#6787)
[FIX] IMPORTANT: rgb normalization
2024-02-09 16:55:37 +01:00
Dhruv Nair
ab7113487c More IPAdapter test fixes (#6888)
update
2024-02-09 13:54:58 +05:30
camaro
59c307f1d5 Standardize model card for Controlnet (#6910)
* controlnet

* style

---------

Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
2024-02-09 12:29:08 +05:30
Sayak Paul
159885adc6 correct hub_token exposition behaviour (thanks to @bghira). (#6918) 2024-02-08 18:38:27 -10:00
Aryan
7337eea59b [refactor] unnecessary lines in decode_latents in video pipelines (#6682)
* refactor decode latents in video pipelines

* make fix-copies
2024-02-08 17:10:52 -10:00
camaro
f07899a57c Standardize model card for Controlnet SDXL (#6908)
controlnet-sdxl
2024-02-09 07:53:39 +05:30
camaro
a83cc0c0bc Standardize model card for Controlnet flax (#6909)
* controlnet-flax

* style

---------

Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
2024-02-09 07:52:56 +05:30
C Q
db5194a45d Fix Compatibility Issues in stable_diffusion_xl_reference.py (#6251)
* Fix Compatibility Issues in stable_diffusion_xl_reference.py

---------

Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>
2024-02-08 10:52:59 -10:00
shaoxiaowang
e6c9c2513f fix examples/community/pipeline_stable_diffusion_xl_instantid.py (#6759)
Co-authored-by: wangshaoxiao <wangshaoxiao@xiaomi.com>
2024-02-08 10:09:40 -10:00
Kyunghwan Kim
d643b6691f Add vae tiling and slicing in img2img and inpaint (#6871)
* Add vae tiling in img2img and inpaint

* Add vae tiling not slicing
2024-02-08 09:50:00 -10:00
Michael
f5c9be3a0a Remove <cat-toy> validation prompt from examples/textual_inversion/textual_inversion_sdxl.py (#6877)
Remove <cat-toy> validation prompt from textual_inversion_sdxl.py

The `<cat-toy>` validation prompt is a default choice for the example task in the README. But no other part of `textual_inversion_sdxl.py` references the cat toy and `textual_inversion.py` has a default validation prompt of `None` as well.

So bring `textual_inversion_sdxl.py` in line with `textual_inversion.py` and change default validation prompt to `None`
2024-02-08 09:46:06 -10:00
Laisky.Cai
1824d0050e fix: load_image should support PIL Image (#6904)
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
2024-02-08 08:25:37 -10:00
Sayak Paul
30e5e81d58 change to 2024 in the license (#6902)
change to 2024
2024-02-08 08:19:31 -10:00
Masamune Ishihara
8de78001df Add fps argument to export_to_gif function. (#6786) 2024-02-08 21:59:51 +05:30
Patryk Bartkowiak
3ac2357794 changed positional parameters to named parameters like in docs (#6905)
Co-authored-by: Patryk Bartkowiak <patryk.bartkowiak@tcl.com>
Co-authored-by: Linoy Tsaban <57615435+linoytsaban@users.noreply.github.com>
2024-02-08 21:39:03 +05:30
Ehsan Akhgari
17808a091e Fix bug when converting checkpoint to diffusers format (#6900)
This fixes #6899.
2024-02-08 18:52:11 +05:30
Sayak Paul
491a933a1b [I2VGenXL] attention_head_dim in the UNet (#6872)
* attention_head_dim

* debug

* print more info

* correct num_attention_heads behaviour

* down_block_num_attention_heads -> num_attention_heads.

* correct the image link in doc.

* add: deprecation for num_attention_head

* fix: test argument to use attention_head_dim

* more fixes.

* quality

* address comments.

* remove depcrecation.
2024-02-08 12:30:14 +05:30
Sayak Paul
aa82df52e7 [IP Adapters] introduce ip_adapter_image_embeds in the SD pipeline call (#6868)
* add: support for passing ip adapter image embeddings

* debugging

* make feature_extractor unloading conditioned on safety_checker

* better condition

* type annotation

* index to look into value slices

* more debugging

* debugging

* serialize embeddings dict

* better conditioning

* remove unnecessary prints.

* Update src/diffusers/loaders/ip_adapter.py

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

* make fix-copies and styling.

* styling and further copy fixing.

* fix: check_inputs call in controlnet sdxl img2img pipeline

---------

Co-authored-by: YiYi Xu <yixu310@gmail.com>
2024-02-08 11:10:10 +05:30
Srimanth Agastyaraju
a11b0f83b7 Fix: training resume from fp16 for SDXL Consistency Distillation (#6840)
* Fix: training resume from fp16 for lcm distill lora sdxl

* Fix coding quality - run linter

* Fix 1 - shift mixed precision cast before optimizer

* Fix 2 - State dict errors by removing load_lora_into_unet

* Update train_lcm_distill_lora_sdxl.py - Revert default cache dir to None

---------

Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
2024-02-08 11:09:29 +05:30
Sayak Paul
1835510524 Remove torch_dtype in to() to end deprecation (#6886)
* remove torch_dtype from to()

* remove torch_dtype from usage scripts.

* remove old lora backend

* Revert "remove old lora backend"

This reverts commit adcddf6ba4.
2024-02-08 09:38:57 +05:30
camaro
4a3d52850b fix: keyword argument mismatch (#6895) 2024-02-08 09:37:56 +05:30
YiYi Xu
97d004b9b4 [ip-adapter] make sure length of scale is same as number of ip-adapters when using set_ip_adapter_scale (#6884)
add

Co-authored-by: yiyixuxu <yixu310@gmail,com>
2024-02-07 10:13:12 -10:00
Sayak Paul
76696dca55 [Model Card] standardize dreambooth model card (#6729)
* feat: standarize model card creation for dreambooth training.

* correct 'inference

* remove comments.

* take component out of kwargs

* style

* add: card template to have a leaner description.

* widget support.

* propagate changes to train_dreambooth_lora

* propagate changes to custom diffusion

* make widget properly type-annotated
2024-02-07 15:07:11 +05:30
Félix Sanz
17612de451 fix: typo in callback function name and property (#6834)
* fix: callback function name is incorrect

On this tutorial there is a function defined and then used inside `callback_on_step_end` argument, but the name was not correct (mismatch)

* fix: typo in num_timestep (correct is num_timesteps)

fixed property name
2024-02-06 12:05:40 -08:00
Dhruv Nair
994360f7a5 Fix last IP Adapter test (#6875)
update
2024-02-06 08:53:40 -10:00
Dhruv Nair
e6a48db633 Refactor Deepfloyd IF tests. (#6855)
* update

* update

* update
2024-02-06 16:43:17 +05:30
sayakpaul
4f1df69d1a Revert "add attention_head_dim"
This reverts commit 15f6b22466.
2024-02-06 14:48:49 +05:30
sayakpaul
15f6b22466 add attention_head_dim 2024-02-06 14:48:07 +05:30
Sayak Paul
e6fd9ada3a [I2vGenXL] clean up things (#6845)
* remove _to_tensor

* remove _to_tensor definition

* remove _collapse_frames_into_batch

* remove lora for not bloating the code.

* remove sample_size.

* simplify code a bit more

* ensure timesteps are always in tensor.
2024-02-06 09:22:07 +05:30
Edward Li
493228a708 Fix AutoencoderTiny with use_slicing (#6850)
* Fix `AutoencoderTiny` with `use_slicing`

When using slicing with AutoencoderTiny, the encoder mistakenly encodes the entire batch for every image in the batch.

* Fixed formatting issue
2024-02-05 09:18:22 -10:00
Dhruv Nair
8bf046b7fb Add single file and IP Adapter support to PIA Pipeline (#6851)
update
2024-02-05 16:23:18 +05:30
Dhruv Nair
bb99623d09 Update IP Adapter tests to use cosine similarity distance (#6806)
* update

* update
2024-02-05 16:22:59 +05:30
Dhruv Nair
fdf55b1f1c Fix posix path issue in testing utils (#6849)
update
2024-02-05 08:57:18 +05:30
小咩Goat
c6f8c310c3 Fix forward pass in UNetMotionModel when gradient checkpoint is enabled (#6744)
fix #6742

Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
2024-02-05 08:04:01 +05:30
YiYi Xu
64909f17b7 update IP-adapter code in UNetMotionModel (#6828)
fix

Co-authored-by: yiyixuxu <yixu310@gmail,com>
2024-02-05 07:26:46 +05:30
Dhruv Nair
f09ca909c8 Multiple small fixes to Video Pipeline docs (#6805)
* update

* update

* update

* Update src/diffusers/pipelines/i2vgen_xl/pipeline_i2vgen_xl.py

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

* update

* update

---------

Co-authored-by: YiYi Xu <yixu310@gmail.com>
2024-02-05 07:24:38 +05:30
YiYi Xu
a5fc62f819 add self.use_ada_layer_norm_* params back to BasicTransformerBlock (#6841)
fix sd reference community ppeline

Co-authored-by: yiyixuxu <yixu310@gmail,com>
2024-02-04 11:16:44 -10:00
Linoy Tsaban
fbdf26bac5 [dreambooth lora sdxl] add sdxl micro conditioning (#6795)
* add micro conditioning

* remove redundant lines

* style

* fix missing 's'

* fix missing shape bug due to missing RGB if statement

* remove redundant if, change arg order

---------

Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
2024-02-04 16:00:09 +02:00
Fabio Rigano
13001ee315 Bugfix in IPAdapterFaceID (#6835) 2024-02-03 08:56:55 -10:00
Linoy Tsaban
65329aed98 [advanced dreambooth lora sdxl script] new features + bug fixes (#6691)
* add noise_offset param

* micro conditioning - wip

* image processing adjusted and moved to support micro conditioning

* change time ids to be computed inside train loop

* change time ids to be computed inside train loop

* change time ids to be computed inside train loop

* time ids shape fix

* move token replacement of validation prompt to the same section of instance prompt and class prompt

* add offset noise to sd15 advanced script

* fix token loading during validation

* fix token loading during validation in sdxl script

* a little clean

* style

* a little clean

* style

* sdxl script - a little clean + minor path fix

sd 1.5 script - change default resolution value

* ad 1.5 script - minor path fix

* fix missing comma in code example in model card

* clean up commented lines

* style

* remove time ids computed outside training loop - no longer used now that we utilize micro-conditioning, as all time ids are now computed inside the training loop

* style

* [WIP] - added draft readme, building off of examples/dreambooth/README.md

* readme

* readme

* readme

* readme

* readme

* readme

* readme

* readme

* removed --crops_coords_top_left from CLI args

* style

* fix missing shape bug due to missing RGB if statement

* add blog mention at the start of the reamde as well

* Update examples/advanced_diffusion_training/README.md

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

* change note to render nicely as well

---------

Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
2024-02-03 17:33:43 +02:00
Stephen
02338c9317 Change path to posix (testing_utils.py) (#6803)
change path to pathlib as_posix

Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
2024-02-03 12:44:13 +05:30
Younes Belkada
15ed53d272 Fixes LoRA SDXL training script with DDP + PEFT (#6816)
Update train_dreambooth_lora_sdxl.py
2024-02-03 09:46:32 +05:30
UmerHA
9cc59ba089 [Contributor Experience] Fix test collection on MPS (#6808)
* Update testing_utils.py

* Update testing_utils.py
2024-02-02 20:59:00 +05:30
YiYi Xu
adcbe674a4 [refactor]Scheduler.set_begin_index (#6728) 2024-02-01 09:51:02 -10:00
Sayak Paul
ec9840a5db [Refactor] harmonize the module structure for models in tests (#6738)
* harmonize the module structure for models in tests

* make the folders modules.

---------

Co-authored-by: YiYi Xu <yixu310@gmail.com>
2024-02-01 14:23:39 +05:30
YiYi Xu
093a03a1a1 add is_torchvision_available (#6800)
* add

* remove transformer

---------

Co-authored-by: yiyixuxu <yixu310@gmail,com>
2024-01-31 20:01:44 -10:00
Patrick von Platen
c3369f5673 fix torchvision import (#6796) 2024-01-31 12:13:10 -10:00
Sayak Paul
04cd6adf8c [Feat] add I2VGenXL for image-to-video generation (#6665)
---------

Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>
2024-01-31 10:38:51 -10:00
YiYi Xu
66722dbea7 [sdxl k-diffusion pipeline]move sigma to device (#6757)
move sigma to device

Co-authored-by: yiyixuxu <yixu310@gmail,com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
2024-01-31 09:29:15 -10:00
YiYi Xu
2e8d18e699 [IP-Adapter] Support multiple IP-Adapters (#6573)
---------

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>
2024-01-31 07:11:15 -10:00
Steven Liu
03373de0db [docs] Add missing parameter (#6775)
add missing param
2024-01-31 08:53:40 -08:00
Dhruv Nair
56bea6b4a1 Add PIA Model/Pipeline (#6698)
* update

* update

* updaet

* add tests and docs

* clean up

* add to toctree

* fix copies

* pr review feedback

* fix copies

* fix tests

* update docs

* update

* update

* update docs

* update

* update

* update

* update
2024-01-31 18:00:17 +02:00
Dhruv Nair
d7dc0ffd79 Fix setting scaling factor in VAE config (#6779)
fix
2024-01-31 19:47:22 +05:30
Kashif Rasul
97ee616971 add ipo, hinge and cpo loss to dpo trainer (#6788)
add ipo and hinge loss to dpo trainer
2024-01-31 16:41:31 +05:30
Sayak Paul
0fc62d1702 [Kandinsky tests] add is_flaky to test_model_cpu_offload_forward_pass (#6762)
* add is_flaky to test_model_cpu_offload_forward_pass

* style

* update

---------

Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
2024-01-31 14:51:12 +05:30
Dhruv Nair
f4d3f913f4 Pin torch < 2.2.0 in test runners (#6780)
* update

* update

---------

Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
2024-01-31 13:41:18 +05:30
Viet Nguyen
1cab64b3be Update train_diffusion_dpo.py (#6754)
* Update train_diffusion_dpo.py

Address #6702

* Update train_diffusion_dpo_sdxl.py

* Empty-Commit

---------

Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
2024-01-31 12:46:23 +05:30
Sayak Paul
8d7dc85312 add note about serialization (#6764) 2024-01-31 12:45:40 +05:30
dg845
87a92f779c Fix bug in ResnetBlock2D.forward where LoRA Scale gets Overwritten (#6736)
Fix bug in ResnetBlock2D.forward when not USE_PEFT_BACKEND and using scale_shift for time emb where the lora scale  gets overwritten.

Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
2024-01-30 14:43:48 -10:00
Yunxuan Xiao
0db766ba77 [DDPMScheduler] Load alpha_cumprod to device to avoid redundant data movement. (#6704)
* load cumprod tensor to device

Signed-off-by: woshiyyya <xiaoyunxuan1998@gmail.com>

* fixing ci

Signed-off-by: woshiyyya <xiaoyunxuan1998@gmail.com>

* make fix-copies

Signed-off-by: woshiyyya <xiaoyunxuan1998@gmail.com>

---------

Signed-off-by: woshiyyya <xiaoyunxuan1998@gmail.com>
2024-01-30 13:19:37 -10:00
Dhruv Nair
8e94663503 Update export to video to support new tensor_to_vid function in video pipelines (#6715)
update
2024-01-30 19:43:33 +05:30
YiYi Xu
b09b90e24c udpate ip-adapter slow tests (#6760)
* udpate slices

* up

* hopefully last one

---------

Co-authored-by: yiyixuxu <yixu310@gmail,com>
2024-01-29 17:55:41 -10:00
Sajad Norouzi
058b47553e Fix mixed precision fine-tuning for text-to-image-lora-sdxl example. (#6751)
* Fix mixed precision fine-tuning for text-to-image-lora-sdxl example.

* fix text_encoder_two bug.

---------

Co-authored-by: Sajad Norouzi <sajadn@dev-dsk-sajadn-2a-87239470.us-west-2.amazon.com>
2024-01-30 06:55:02 +05:30
xhedit
7f58a76f48 Update lora.md with a more accurate description of rank (#6724)
* Update lora.md with a more accurate description of rank

* Update docs/source/en/training/lora.md

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

---------

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
2024-01-29 09:41:51 -08:00
Sayak Paul
09b7bfce91 [Core] move transformer scripts to transformers modules (#6747)
* move transformer scripts to transformers modules

* move transformer model test

* move prior transformer test to  directory

* fix doc path

* correct doc path

* add: __init__.py
2024-01-29 22:28:28 +05:30
Fabio Rigano
5d8b1987ec Add unload_textual_inversion method (#6656)
* Add unload_textual_inversion

* Fix dicts in tokenizer

* Fix quality

* Apply suggestions from code review

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

* Fix variable name after last update

---------

Co-authored-by: YiYi Xu <yixu310@gmail.com>
2024-01-29 06:26:22 -10:00
Sayak Paul
acd1962769 correct hflip arg (#6743) 2024-01-28 17:42:34 +05:30
Stephen
5b1b80a5b6 Change os.path to pathlib Path (#6737)
Change os.path to pathlib
2024-01-28 10:24:13 +05:30
gzguevara
8581d9bce4 changed to posix unet (#6719)
changed to posix

Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
2024-01-27 16:31:52 +05:30
Yingtian Liu
c101066227 Correct SNR weighted loss in v-prediction case by only adding 1 to SNR on the denominator (#6307)
* fix minsnr implementation for v-prediction case

* format code

* always compute snr when snr_gamma is specified

---------

Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
2024-01-27 09:18:09 +05:30
Sayak Paul
d4c7ab7bf1 [Hub] feat: explicitly tag to diffusers when using push_to_hub (#6678)
* feat: explicitly tag to diffusers when using push_to_hub

* remove tags.

* reset repo.

* Apply suggestions from code review

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

* fix: tests

* fix: push_to_hub behaviour for tagging from save_pretrained

* Apply suggestions from code review

Co-authored-by: Lucain <lucainp@gmail.com>

* Apply suggestions from code review

Co-authored-by: Lucain <lucainp@gmail.com>

* import fixes.

* add library name to existing model card.

* add: standalone test for generate_model_card

* fix tests for standalone method

* moved library_name to a better place.

* merge create_model_card and generate_model_card.

* fix test

* address lucain's comments

* fix return identation

* Apply suggestions from code review

Co-authored-by: Lucain <lucainp@gmail.com>

* address further comments.

* Update src/diffusers/pipelines/pipeline_utils.py

Co-authored-by: Lucain <lucainp@gmail.com>

---------

Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Lucain <lucainp@gmail.com>
2024-01-26 23:01:48 +05:30
dg845
ea9dc3fa90 Add UFOGenScheduler to Community Examples (#6650)
* Add UFOGenScheduler with diffusers imports changed from relative to absolute.

* make style

* Add community README entry for UFOGenScheduler.
2024-01-26 15:11:14 +02:00
dg845
b4220e97b1 Add Community Example Consistency Training Script (#6717)
* initial commit for unconditional/class-conditional consistency training script

* make style

* Add entry for consistency training script in community README.

* Move consistency training script from community to research_projects/consistency_training

* Add requirements.txt and README to research_projects/consistency_training directory.

* Manually revert community README changes for consistency training.

* Fix path to script after moving script to research projects.

* Add option to load U-Net weights from pretrained model.

---------

Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
2024-01-26 15:10:57 +02:00
Dhruv Nair
dc85b578c2 Move tests for SD inference variant pipelines into their own modules (#6707)
* update

* update

* update
2024-01-26 14:09:41 +02:00
Dhruv Nair
0d927c7542 Add IP Adapters to slow tests (#6714)
update
2024-01-25 19:52:50 -10:00
Andrew Ishutin
5b93338235 fix custom diffusion training with concept list (#6710)
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
2024-01-26 11:17:51 +08:00
818 changed files with 13176 additions and 8717 deletions

View File

@@ -34,11 +34,6 @@ jobs:
runner: docker-cpu
image: diffusers/diffusers-pytorch-cpu
report: torch_cpu_models_schedulers
- name: LoRA
framework: lora
runner: docker-cpu
image: diffusers/diffusers-pytorch-cpu
report: torch_cpu_lora
- name: Fast Flax CPU tests
framework: flax
runner: docker-cpu
@@ -94,14 +89,6 @@ jobs:
--make-reports=tests_${{ matrix.config.report }} \
tests/models tests/schedulers tests/others
- name: Run fast PyTorch LoRA CPU tests
if: ${{ matrix.config.framework == 'lora' }}
run: |
python -m pytest -n 2 --max-worker-restart=0 --dist=loadfile \
-s -v -k "not Flax and not Onnx and not Dependency" \
--make-reports=tests_${{ matrix.config.report }} \
tests/lora
- name: Run fast Flax TPU tests
if: ${{ matrix.config.framework == 'flax' }}
run: |

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@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -24,9 +24,9 @@ ENV PATH="/opt/venv/bin:$PATH"
# pre-install the heavy dependencies (these can later be overridden by the deps from setup.py)
RUN python3 -m pip install --no-cache-dir --upgrade pip && \
python3 -m pip install --no-cache-dir \
torch \
torchvision \
torchaudio \
torch==2.1.2 \
torchvision==0.16.2 \
torchaudio==2.1.2 \
onnxruntime \
--extra-index-url https://download.pytorch.org/whl/cpu && \
python3 -m pip install --no-cache-dir \

View File

@@ -24,9 +24,9 @@ ENV PATH="/opt/venv/bin:$PATH"
# pre-install the heavy dependencies (these can later be overridden by the deps from setup.py)
RUN python3 -m pip install --no-cache-dir --upgrade pip && \
python3 -m pip install --no-cache-dir \
torch \
torchvision \
torchaudio \
torch==2.1.2 \
torchvision==0.16.2 \
torchaudio==2.1.2 \
"onnxruntime-gpu>=1.13.1" \
--extra-index-url https://download.pytorch.org/whl/cu117 && \
python3 -m pip install --no-cache-dir \

View File

@@ -40,6 +40,6 @@ RUN python3.9 -m pip install --no-cache-dir --upgrade pip && \
numpy \
scipy \
tensorboard \
transformers
transformers
CMD ["/bin/bash"]

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@@ -1,5 +1,5 @@
<!---
Copyright 2023- The HuggingFace Team. All rights reserved.
Copyright 2024- The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -284,6 +284,8 @@
title: DiffEdit
- local: api/pipelines/dit
title: DiT
- local: api/pipelines/i2vgenxl
title: I2VGen-XL
- local: api/pipelines/pix2pix
title: InstructPix2Pix
- local: api/pipelines/kandinsky
@@ -302,6 +304,8 @@
title: MusicLDM
- local: api/pipelines/paint_by_example
title: Paint by Example
- local: api/pipelines/pia
title: Personalized Image Animator (PIA)
- local: api/pipelines/pixart
title: PixArt-α
- local: api/pipelines/self_attention_guidance

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
@@ -24,4 +24,4 @@ The abstract from the paper is:
## PriorTransformerOutput
[[autodoc]] models.prior_transformer.PriorTransformerOutput
[[autodoc]] models.transformers.prior_transformer.PriorTransformerOutput

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
@@ -38,4 +38,4 @@ It is assumed one of the input classes is the masked latent pixel. The predicted
## Transformer2DModelOutput
[[autodoc]] models.transformer_2d.Transformer2DModelOutput
[[autodoc]] models.transformers.transformer_2d.Transformer2DModelOutput

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
@@ -16,8 +16,8 @@ A Transformer model for video-like data.
## TransformerTemporalModel
[[autodoc]] models.transformer_temporal.TransformerTemporalModel
[[autodoc]] models.transformers.transformer_temporal.TransformerTemporalModel
## TransformerTemporalModelOutput
[[autodoc]] models.transformer_temporal.TransformerTemporalModelOutput
[[autodoc]] models.transformers.transformer_temporal.TransformerTemporalModelOutput

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -0,0 +1,57 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
specific language governing permissions and limitations under the License.
-->
# I2VGen-XL
[I2VGen-XL: High-Quality Image-to-Video Synthesis via Cascaded Diffusion Models](https://hf.co/papers/2311.04145.pdf) by Shiwei Zhang, Jiayu Wang, Yingya Zhang, Kang Zhao, Hangjie Yuan, Zhiwu Qin, Xiang Wang, Deli Zhao, and Jingren Zhou.
The abstract from the paper is:
*Video synthesis has recently made remarkable strides benefiting from the rapid development of diffusion models. However, it still encounters challenges in terms of semantic accuracy, clarity and spatio-temporal continuity. They primarily arise from the scarcity of well-aligned text-video data and the complex inherent structure of videos, making it difficult for the model to simultaneously ensure semantic and qualitative excellence. In this report, we propose a cascaded I2VGen-XL approach that enhances model performance by decoupling these two factors and ensures the alignment of the input data by utilizing static images as a form of crucial guidance. I2VGen-XL consists of two stages: i) the base stage guarantees coherent semantics and preserves content from input images by using two hierarchical encoders, and ii) the refinement stage enhances the video's details by incorporating an additional brief text and improves the resolution to 1280×720. To improve the diversity, we collect around 35 million single-shot text-video pairs and 6 billion text-image pairs to optimize the model. By this means, I2VGen-XL can simultaneously enhance the semantic accuracy, continuity of details and clarity of generated videos. Through extensive experiments, we have investigated the underlying principles of I2VGen-XL and compared it with current top methods, which can demonstrate its effectiveness on diverse data. The source code and models will be publicly available at [this https URL](https://i2vgen-xl.github.io/).*
The original codebase can be found [here](https://github.com/ali-vilab/i2vgen-xl/). The model checkpoints can be found [here](https://huggingface.co/ali-vilab/).
<Tip>
Make sure to check out the Schedulers [guide](../../using-diffusers/schedulers) to learn how to explore the tradeoff between scheduler speed and quality, and see the [reuse components across pipelines](../../using-diffusers/loading#reuse-components-across-pipelines) section to learn how to efficiently load the same components into multiple pipelines. Also, to know more about reducing the memory usage of this pipeline, refer to the ["Reduce memory usage"] section [here](../../using-diffusers/svd#reduce-memory-usage).
</Tip>
Sample output with I2VGenXL:
<table>
<tr>
<td><center>
library.
<br>
<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/i2vgen-xl-example.gif"
alt="library"
style="width: 300px;" />
</center></td>
</tr>
</table>
## Notes
* I2VGenXL always uses a `clip_skip` value of 1. This means it leverages the penultimate layer representations from the text encoder of CLIP.
* It can generate videos of quality that is often on par with [Stable Video Diffusion](../../using-diffusers/svd) (SVD).
* Unlike SVD, it additionally accepts text prompts as inputs.
* It can generate higher resolution videos.
* When using the [`DDIMScheduler`] (which is default for this pipeline), less than 50 steps for inference leads to bad results.
## I2VGenXLPipeline
[[autodoc]] I2VGenXLPipeline
- all
- __call__
## I2VGenXLPipelineOutput
[[autodoc]] pipelines.i2vgen_xl.pipeline_i2vgen_xl.I2VGenXLPipelineOutput

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@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -1,4 +1,4 @@
<!--Copyright 2023 The HuggingFace Team. All rights reserved.
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at

View File

@@ -0,0 +1,167 @@
<!--Copyright 2024 The HuggingFace Team. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the
specific language governing permissions and limitations under the License.
-->
# Image-to-Video Generation with PIA (Personalized Image Animator)
## Overview
[PIA: Your Personalized Image Animator via Plug-and-Play Modules in Text-to-Image Models](https://arxiv.org/abs/2312.13964) by Yiming Zhang, Zhening Xing, Yanhong Zeng, Youqing Fang, Kai Chen
Recent advancements in personalized text-to-image (T2I) models have revolutionized content creation, empowering non-experts to generate stunning images with unique styles. While promising, adding realistic motions into these personalized images by text poses significant challenges in preserving distinct styles, high-fidelity details, and achieving motion controllability by text. In this paper, we present PIA, a Personalized Image Animator that excels in aligning with condition images, achieving motion controllability by text, and the compatibility with various personalized T2I models without specific tuning. To achieve these goals, PIA builds upon a base T2I model with well-trained temporal alignment layers, allowing for the seamless transformation of any personalized T2I model into an image animation model. A key component of PIA is the introduction of the condition module, which utilizes the condition frame and inter-frame affinity as input to transfer appearance information guided by the affinity hint for individual frame synthesis in the latent space. This design mitigates the challenges of appearance-related image alignment within and allows for a stronger focus on aligning with motion-related guidance.
[Project page](https://pi-animator.github.io/)
## Available Pipelines
| Pipeline | Tasks | Demo
|---|---|:---:|
| [PIAPipeline](https://github.com/huggingface/diffusers/blob/main/src/diffusers/pipelines/pia/pipeline_pia.py) | *Image-to-Video Generation with PIA* |
## Available checkpoints
Motion Adapter checkpoints for PIA can be found under the [OpenMMLab org](https://huggingface.co/openmmlab/PIA-condition-adapter). These checkpoints are meant to work with any model based on Stable Diffusion 1.5
## Usage example
PIA works with a MotionAdapter checkpoint and a Stable Diffusion 1.5 model checkpoint. The MotionAdapter is a collection of Motion Modules that are responsible for adding coherent motion across image frames. These modules are applied after the Resnet and Attention blocks in the Stable Diffusion UNet. In addition to the motion modules, PIA also replaces the input convolution layer of the SD 1.5 UNet model with a 9 channel input convolution layer.
The following example demonstrates how to use PIA to generate a video from a single image.
```python
import torch
from diffusers import (
EulerDiscreteScheduler,
MotionAdapter,
PIAPipeline,
)
from diffusers.utils import export_to_gif, load_image
adapter = MotionAdapter.from_pretrained("openmmlab/PIA-condition-adapter")
pipe = PIAPipeline.from_pretrained("SG161222/Realistic_Vision_V6.0_B1_noVAE", motion_adapter=adapter, torch_dtype=torch.float16)
pipe.scheduler = EulerDiscreteScheduler.from_config(pipe.scheduler.config)
pipe.enable_model_cpu_offload()
pipe.enable_vae_slicing()
image = load_image(
"https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/pix2pix/cat_6.png?download=true"
)
image = image.resize((512, 512))
prompt = "cat in a field"
negative_prompt = "wrong white balance, dark, sketches,worst quality,low quality"
generator = torch.Generator("cpu").manual_seed(0)
output = pipe(image=image, prompt=prompt, generator=generator)
frames = output.frames[0]
export_to_gif(frames, "pia-animation.gif")
```
Here are some sample outputs:
<table>
<tr>
<td><center>
cat in a field.
<br>
<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/pia-default-output.gif"
alt="cat in a field"
style="width: 300px;" />
</center></td>
</tr>
</table>
<Tip>
If you plan on using a scheduler that can clip samples, make sure to disable it by setting `clip_sample=False` in the scheduler as this can also have an adverse effect on generated samples. Additionally, the PIA checkpoints can be sensitive to the beta schedule of the scheduler. We recommend setting this to `linear`.
</Tip>
## Using FreeInit
[FreeInit: Bridging Initialization Gap in Video Diffusion Models](https://arxiv.org/abs/2312.07537) by Tianxing Wu, Chenyang Si, Yuming Jiang, Ziqi Huang, Ziwei Liu.
FreeInit is an effective method that improves temporal consistency and overall quality of videos generated using video-diffusion-models without any addition training. It can be applied to PIA, AnimateDiff, ModelScope, VideoCrafter and various other video generation models seamlessly at inference time, and works by iteratively refining the latent-initialization noise. More details can be found it the paper.
The following example demonstrates the usage of FreeInit.
```python
import torch
from diffusers import (
DDIMScheduler,
MotionAdapter,
PIAPipeline,
)
from diffusers.utils import export_to_gif, load_image
adapter = MotionAdapter.from_pretrained("openmmlab/PIA-condition-adapter")
pipe = PIAPipeline.from_pretrained("SG161222/Realistic_Vision_V6.0_B1_noVAE", motion_adapter=adapter)
# enable FreeInit
# Refer to the enable_free_init documentation for a full list of configurable parameters
pipe.enable_free_init(method="butterworth", use_fast_sampling=True)
# Memory saving options
pipe.enable_model_cpu_offload()
pipe.enable_vae_slicing()
pipe.scheduler = DDIMScheduler.from_config(pipe.scheduler.config)
image = load_image(
"https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/pix2pix/cat_6.png?download=true"
)
image = image.resize((512, 512))
prompt = "cat in a field"
negative_prompt = "wrong white balance, dark, sketches,worst quality,low quality"
generator = torch.Generator("cpu").manual_seed(0)
output = pipe(image=image, prompt=prompt, generator=generator)
frames = output.frames[0]
export_to_gif(frames, "pia-freeinit-animation.gif")
```
<table>
<tr>
<td><center>
cat in a field.
<br>
<img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/pia-freeinit-output-cat.gif"
alt="cat in a field"
style="width: 300px;" />
</center></td>
</tr>
</table>
<Tip warning={true}>
FreeInit is not really free - the improved quality comes at the cost of extra computation. It requires sampling a few extra times depending on the `num_iters` parameter that is set when enabling it. Setting the `use_fast_sampling` parameter to `True` can improve the overall performance (at the cost of lower quality compared to when `use_fast_sampling=False` but still better results than vanilla video generation models).
</Tip>
## PIAPipeline
[[autodoc]] PIAPipeline
- all
- __call__
- enable_freeu
- disable_freeu
- enable_free_init
- disable_free_init
- enable_vae_slicing
- disable_vae_slicing
- enable_vae_tiling
- disable_vae_tiling
## PIAPipelineOutput
[[autodoc]] pipelines.pia.PIAPipelineOutput

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@@ -41,7 +41,7 @@ pipe = DiffusionPipeline.from_pretrained("damo-vilab/text-to-video-ms-1.7b", tor
pipe = pipe.to("cuda")
prompt = "Spiderman is surfing"
video_frames = pipe(prompt).frames
video_frames = pipe(prompt).frames[0]
video_path = export_to_video(video_frames)
video_path
```
@@ -64,7 +64,7 @@ pipe.enable_model_cpu_offload()
pipe.enable_vae_slicing()
prompt = "Darth Vader surfing a wave"
video_frames = pipe(prompt, num_frames=64).frames
video_frames = pipe(prompt, num_frames=64).frames[0]
video_path = export_to_video(video_frames)
video_path
```
@@ -83,7 +83,7 @@ pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
pipe.enable_model_cpu_offload()
prompt = "Spiderman is surfing"
video_frames = pipe(prompt, num_inference_steps=25).frames
video_frames = pipe(prompt, num_inference_steps=25).frames[0]
video_path = export_to_video(video_frames)
video_path
```
@@ -130,7 +130,7 @@ pipe.unet.enable_forward_chunking(chunk_size=1, dim=1)
pipe.enable_vae_slicing()
prompt = "Darth Vader surfing a wave"
video_frames = pipe(prompt, num_frames=24).frames
video_frames = pipe(prompt, num_frames=24).frames[0]
video_path = export_to_video(video_frames)
video_path
```
@@ -148,7 +148,7 @@ pipe.enable_vae_slicing()
video = [Image.fromarray(frame).resize((1024, 576)) for frame in video_frames]
video_frames = pipe(prompt, video=video, strength=0.6).frames
video_frames = pipe(prompt, video=video, strength=0.6).frames[0]
video_path = export_to_video(video_frames)
video_path
```

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