GitLab

* 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

decorate UNetControlNetXSModelTests::test_forward_no_control with is_flaky

update

* style


* Fix device map nits (#7705)


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

* Switch to peft and multi proj layers

* Move Face ID loading and inference to core

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

* CheckIn - created DownSubBlocks

* Added extra channels, implemented subblock fwd

* Fixed connection sizes

* checkin

* Removed iter, next in forward

* Models for SD21 & SDXL run through

* Added back pipelines, cleared up connections

* Cleaned up connection creation

* added debug logs

* updated logs

* logs: added input loading

* Update umer_debug_logger.py

* log: Loading hint

* Update umer_debug_logger.py

* added logs

* Changed debug logging

* debug: added more logs

* Fixed num_norm_groups

* Debug: Logging all of SDXL input

* Update umer_debug_logger.py

* debug: updated logs

* checkim

* Readded tests

* Removed debug logs

* Fixed Slow Tests

* Added value ckecks | Updated model_cpu_offload_seq

* accelerate-offloading works ; fast tests work

* Made unet & addon explicit in controlnet

* Updated slow tests

* Added dtype/device to ControlNetXS

* Filled in test model paths

* Added image_encoder/feature_extractor to XL pipe

* Fixed fast tests

* Added comments and docstrings

* Fixed copies

* Added docs ; Updates slow tests

* Moved changes to UNetMidBlock2DCrossAttn

* tiny cleanups

* Removed stray prints

* Removed ip adapters + freeU

- Removed ip adapters + freeU as they don't make sense for ControlNet-XS
- Fixed imports of UNet components

* Fixed test_save_load_float16

* Make style, quality, fix-copies

* Changed loading/saving API for ControlNetXS

- Changed loading/saving API for ControlNetXS
- other small fixes

* Removed ControlNet-XS from research examples

* Make style, quality, fix-copies

* Small fixes

- deleted ControlNetXSModel.init_original
- added time_embedding_mix to StableDiffusionControlNetXSPipeline .from_pretrained / StableDiffusionXLControlNetXSPipeline.from_pretrained
- fixed copy hints

* checkin May 11 '23

* CheckIn Mar 12 '24

* Fixed tests for SD

* Added tests for UNetControlNetXSModel

* Fixed SDXL tests

* cleanup

* Delete Pipfile

* CheckIn Mar 20

Started replacing sub blocks  by `ControlNetXSCrossAttnDownBlock2D` and `ControlNetXSCrossAttnUplock2D`

* check-in Mar 23

* checkin 24 Mar

* Created init for UNetCnxs and CnxsAddon

* CheckIn

* Made from_modules, from_unet and no_control work

* make style,quality,fix-copies & small changes

* Fixed freezing

* Added gradient ckpt'ing; fixed tests

* Fix slow tests(+compile) ; clear naming confusion

* Don't create UNet in init ; removed class_emb

* Incorporated review feedback

- Deleted get_base_pipeline /  get_controlnet_addon for pipes
- Pipes inherit from StableDiffusionXLPipeline
- Made module dicts for cnxs-addon's down/mid/up classes
- Added support for qkv fusion and freeU

* Make style, quality, fix-copies

* Implemented review feedback

* Removed compatibility check for vae/ctrl embedding

* make style, quality, fix-copies

* Delete Pipfile

* Integrated review feedback

- Importing ControlNetConditioningEmbedding now
- get_down/mid/up_block_addon now outside class
- renamed `do_control` to `apply_control`

* Reduced size of test tensors

For this, added `norm_num_groups` as parameter everywhere

* Renamed cnxs-`Addon` to cnxs-`Adapter`

- `ControlNetXSAddon` -> `ControlNetXSAdapter`
- `ControlNetXSAddonDownBlockComponents` -> `DownBlockControlNetXSAdapter`, and similarly for mid/up
- `get_mid_block_addon` -> `get_mid_block_adapter`, and similarly for mid/up

* Fixed save_pretrained/from_pretrained bug

* Removed redundant code

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

* disable test

* update

---------
Co-authored-by: yiyixuxu <yixu310@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

* update

* update

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

use float16 and add torch.no_grad()

* Fix typos

* Add docstring to `decode` method in `ConsistencyDecoderVAE`

* Fix tiling

* Enable tiled VAE decoding with customizable tile sample size and overlap factor

* Revert "Enable tiled VAE decoding with customizable tile sample size and overlap factor"

This reverts commit 181049675e83cea7b33ae2bbeba2aff7ae1b1761.

* Add VAE tiling test for `ConsistencyDecoderVAE`

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

skip dynamo tests when python is 3.12.

* Fix typos

* Fix typos

* Fix typos

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

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

* update

* update

* update

update

* update

* update

* update

* update

* update

* update

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

* fix PyTorch classes and start deprecsation cycles.

* remove args crafting for accommodating scale.

* remove scale check in feedforward.

* assert against nn.Linear and not CompatibleLinear.

* remove conv_cls and lineaR_cls.

* remove scale

* 👋

 scale.

* fix: unet2dcondition

* fix attention.py

* fix: attention.py again

* fix: unet_2d_blocks.

* fix-copies.

* more fixes.

* fix: resnet.py

* more fixes

* fix i2vgenxl unet.

* depcrecate scale gently.

* fix-copies

* Apply suggestions from code review
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* quality

* throw warning when scale is passed to the the BasicTransformerBlock class.

* remove scale from signature.

* cross_attention_kwargs, very nice catch by Yiyi

* fix: logger.warn

* make deprecation message clearer.

* address final comments.

* maintain same depcrecation message and also add it to activations.

* address yiyi

* fix copies

* Apply suggestions from code review
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* more depcrecation

* fix-copies

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

* update

* update

* update

* update

---------
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>

* 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

* 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>

* move unets to  module 🦋

* parameterize unet-level import.

* fix flax unet2dcondition model import

* models __init__

* mildly depcrecating models.unet_2d_blocks in favor of models.unets.unet_2d_blocks.

* noqa

* correct depcrecation behaviour

* inherit from the actual classes.

* Empty-Commit

* backwards compatibility for unet_2d.py

* backward compatibility for unet_2d_condition

* bc for unet_1d

* bc for unet_1d_blocks

* 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>

* begin model

* finish blocks

* add_embedding

* addition_time_embed_dim

* use TimestepEmbedding

* fix temporal res block

* fix time_pos_embed

* fix add_embedding

* add conversion script

* fix model

* up

* add new resnet blocks

* make forward work

* return sample in original shape

* fix temb shape in TemporalResnetBlock

* add spatio temporal transformers

* add vae blocks

* fix blocks

* update

* update

* fix shapes in Alphablender and add time activation in res blcok

* use new blocks

* style

* fix temb shape

* fix SpatioTemporalResBlock

* reuse TemporalBasicTransformerBlock

* fix TemporalBasicTransformerBlock

* use TransformerSpatioTemporalModel

* fix TransformerSpatioTemporalModel

* fix time_context dim

* clean up

* make temb optional

* add blocks

* rename model

* update conversion script

* remove UNetMidBlockSpatioTemporal

* add in init

* remove unused arg

* remove unused arg

* remove more unsed args

* up

* up

* check for None

* update vae

* update up/mid blocks for decoder

* begin pipeline

* adapt scheduler

* add guidance scalings

* fix norm eps in temporal transformers

* add temporal autoencoder

* make pipeline run

* fix frame decodig

* decode in float32

* decode n frames at a time

* pass decoding_t to decode_latents

* fix decode_latents

* vae encode/decode in fp32

* fix dtype in TransformerSpatioTemporalModel

* type image_latents same as image_embeddings

* allow using differnt eps in temporal block for video decoder

* fix default values in vae

* pass num frames in decode

* switch spatial to temporal for mixing in VAE

* fix num frames during split decoding

* cast alpha to sample dtype

* fix attention in MidBlockTemporalDecoder

* fix typo

* fix guidance_scales dtype

* fix missing activation in TemporalDecoder

* skip_post_quant_conv

* add vae conversion

* style

* take guidance scale as input

* up

* allow passing PIL to export_video

* accept fps as arg

* add pipeline and vae in init

* remove hack

* use AutoencoderKLTemporalDecoder

* don't scale image latents

* add unet tests

* clean up unet

* clean TransformerSpatioTemporalModel

* add slow svd test

* clean up

* make temb optional in Decoder mid block

* fix norm eps in TransformerSpatioTemporalModel

* clean up temp decoder

* clean up

* clean up

* use c_noise values for timesteps

* use math for log

* update

* fix copies

* doc

* upcast vae

* update forward pass for gradient checkpointing

* make added_time_ids is tensor

* up

* fix upcasting

* remove post quant conv

* add _resize_with_antialiasing

* fix _compute_padding

* cleanup model

* more cleanup

* more cleanup

* more cleanup

* remove freeu

* remove attn slice

* small clean

* up

* up

* remove extra step kwargs

* remove eta

* remove dropout

* remove callback

* remove merge factor args

* clean

* clean up

* move to dedicated folder

* remove attention_head_dim

* docstr and small fix

* update unet doc strings

* rename decoding_t

* correct linting

* store c_skip and c_out

* cleanup

* clean TemporalResnetBlock

* more cleanup

* clean up vae

* clean up

* begin doc

* more cleanup

* up

* up

* doc

* Improve

* better naming

* better naming

* better naming

* better naming

* better naming

* better naming

* better naming

* better naming

* Apply suggestions from code review

* Default chunk size to None

* add example

* Better

* Apply suggestions from code review

* update doc

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

* style

* Get torch compile working

* up

* rename

* fix doc

* add chunking

* torch compile

* torch compile

* add modelling outputs

* torch compile

* Improve chunking

* Apply suggestions from code review

* Update docs/source/en/using-diffusers/svd.md

* Close diff tag

* remove slicing

* resnet docstr

* add docstr in resnet

* rename

* Apply suggestions from code review

* update tests

* Fix output type latents

* fix more

* fix more

* Update docs/source/en/using-diffusers/svd.md

* fix more

* add pipeline tests

* remove unused arg

* clean  up

* make sure get_scaling receives tensors

* fix euler scheduler

* fix get_scalings

* simply euler for now

* remove old test file

* use randn_tensor to create noise

* fix device for rand tensor

* increase expected_max_difference

* fix test_inference_batch_single_identical

* actually fix test_inference_batch_single_identical

* disable test_save_load_float16

* skip test_float16_inference

* skip test_inference_batch_single_identical

* fix test_xformers_attention_forwardGenerator_pass

* Apply suggestions from code review

* update StableVideoDiffusionPipelineSlowTests

* update image

* add diffusers example

* fix more

---------
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: apolinário <joaopaulo.passos@gmail.com>

* add comments to explain the code better

* add comments to explain the code better

* add comments to explain the code better

* add comments to explain the code better

* add comments to explain the code better

* fix more

* fix more

* fix more

* fix more

* fix more

* fix more

* 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>

* 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

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

* uP

* Update src/diffusers/models/consistency_decoder_vae.py

* uP

* uP

* consistency decoder

* rename

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

* Update src/diffusers/pipelines/consistency_models/pipeline_consistency_models.py

* uP

* Apply suggestions from code review

* uP

* uP

* uP

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

* fix model xformers test

* update

* draft design

* clean up

* clean up

* clean up

* clean up

* clean up

* clean  up

* clean up

* clean up

* clean up

* update pipeline

* clean up

* clean up

* clean up

* add tests

* change motion block

* clean up

* clean up

* clean up

* update

* update

* update

* update

* update

* update

* update

* update

* clean up

* update

* update

* update model test

* update

* update

* update

* update

* make style

* update

* fix embeddings

* update

* merge upstream

* max fix copies

* fix bug

* fix mistake

* add docs

* update

* clean up

* update

* clean up

* clean up

* fix docstrings

* fix docstrings

* update

* update

* clean  up

* update

* 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>