GitLab

make VAE compatible to torch.compile()
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* Merged isinstance calls to make the code simpler.

* Corrected formatting errors using ruff.

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

* Init commit

* Removed einops

* Added default movq config for training

* Update explanation of prompts

* Fixed inheritance of discriminator and init_tracker

* Fixed incompatible api between muse and here

* Fixed output

* Setup init training

* Basic structure done

* Removed attention for quick tests

* Style fixes

* Fixed vae/vqgan styles

* Removed redefinition of wandb

* Fixed log_validation and tqdm

* Nothing commit

* Added commit loss to lookup_from_codebook

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

* Adding perliminary README

* Fixed one typo

* Local changes

* Fixed main issues

* Merging

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

* Testing+Fixed bugs in training script

* Some style fixes

* Added wandb to docs

* Fixed timm test

* get testing suite ready.

* remove return loss

* remove return_loss

* Remove diffs

* Remove diffs

* fix ruff format

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

separate the loading utilities in modeling similar to pipelines.

* Fix loading from_pipe

* Fix style

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

* find & replace all FloatTensors to Tensor

* apply formatting

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

* formatting

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

* formatting

* Update new file from FloatTensor to Tensor

* refactor unet single file loading a bit.

* retrieve the unet from create_diffusers_unet_model_from_ldm

* update

* update

* updae

* update

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* tests

* update

* update

* update

* Update docs/source/en/api/single_file.md
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Update docs/source/en/api/single_file.md
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* update

* update

* update

* update

* update

* update

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* update

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* update

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* update

* update

* Update docs/source/en/api/loaders/single_file.md
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* Update src/diffusers/loaders/single_file.py
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* Update docs/source/en/api/loaders/single_file.md
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Update docs/source/en/api/loaders/single_file.md
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Update docs/source/en/api/loaders/single_file.md
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Update docs/source/en/api/loaders/single_file.md
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* update

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

* update conversion script to handle motion adapter sdxl checkpoint

* add animatediff xl

* handle addition_embed_type

* fix output

* update

* add imports

* make fix-copies

* add decode latents

* update docstrings

* add animatediff sdxl to docs

* remove unnecessary lines

* update example

* add test

* revert conv_in conv_out kernel param

* remove unused param addition_embed_type_num_heads

* latest IPAdapter impl

* make fix-copies

* fix return

* add IPAdapterTesterMixin to tests

* fix return

* revert based on suggestion

* add freeinit

* fix test_to_dtype test

* use StableDiffusionMixin instead of different helper methods

* fix progress bar iterations

* apply suggestions from review

* hardcode flip_sin_to_cos and freq_shift

* make fix-copies

* fix ip adapter implementation

* fix last failing test

* make style

* Update docs/source/en/api/pipelines/animatediff.md
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* remove todo

* fix doc-builder errors

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

Add Ascend NPU support for SDXL fine-tuning and fix the model saving bug when using DeepSpeed. (#7816)

* Add Ascend NPU support for SDXL fine-tuning and fix the model saving bug when using DeepSpeed.

* fix check code quality

* Decouple the NPU flash attention and make it an independent module.

* add doc and unit tests for npu flash attention.

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Co-authored-by: mhh001 <mahonghao1@huawei.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Deprecate resume_download

* align docstring with transformers

* style

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

* 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

* support PixArt-DMD

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Co-authored-by: jschen <chenjunsong4@h-partners.com>
Co-authored-by: badayvedat <badayvedat@gmail.com>
Co-authored-by: Vedat Baday <54285744+badayvedat@users.noreply.github.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>
Co-authored-by: yiyixuxu <yixu310@gmail,com>

* enable control ip-adapter per-transformer block on-the-fly

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Co-authored-by: sayakpaul <spsayakpaul@gmail.com>
Co-authored-by: ResearcherXman <xhs.research@gmail.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>

Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* update

* update

* style


* Fix device map nits (#7705)


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

* Switch to peft and multi proj layers

* Move Face ID loading and inference to core

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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

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

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

* get device <-> component mapping when using multiple gpus.

* condition the device_map bits.

* relax condition

* device_map progress.

* device_map enhancement

* some cleaning up and debugging

* Apply suggestions from code review
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>

* incorporate suggestions from PR.

* remove multi-gpu condition for now.

* guard check the component -> device mapping

* fix: device_memory variable

* dispatching transformers model to have force_hooks=True

* better guarding for transformers device_map

* introduce support balanced_low_memory and balanced_ultra_low_memory.

* remove device_map patch.

* fix: intermediate variable scoping.

* fix: condition in cpu offload.

* fix: flax class restrictions.

* remove modifications from cpu_offload and model_offload

* incorporate changes.

* add a simple forward pass test

* add: torch_device in get_inputs()

* add: tests

* remove print

* safe-guard to(), model offloading and cpu offloading when balanced is used as a device_map.

* style

* remove .

* safeguard device_map with more checks and remove invalid device_mapping strategues.

* make  a class attribute and adjust tests accordingly.

* fix device_map check

* fix test

* adjust comment

* fix: device_map attribute

* fix: dispatching.

* max_memory test for pipeline

* version guard the tests

* fix guard.

* address review feedback.

* reset_device_map method.

* add: test for reset_hf_device_map

* fix a couple things.

* add reset_device_map() in the error message.

* add tests for checking reset_device_map doesn't have unintended consequences.

* fix reset_device_map and offloading tests.

* create _get_final_device_map utility.

* hf_device_map -> _hf_device_map

* add documentation

* add notes suggested by Marc.

* styling.

* Apply suggestions from code review
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* move updates within gpu condition.

* other docs related things

* note on ignore a device not specified in .

* provide a suggestion if device mapping errors out.

* fix: typo.

* _hf_device_map -> hf_device_map

* Empty-Commit

* add: example hf_device_map.

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Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* refactor transformer_2d forward logic into meaningful conditions.

* Empty-Commit

* fix: _operate_on_patched_inputs

* fix: _operate_on_patched_inputs

* check

* fix: patch output computation block.

* fix: _operate_on_patched_inputs.

* remove print.

* move operations to blocks.

* more readability neats.

* empty commit

* Apply suggestions from code review
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* Revert "Apply suggestions from code review"

This reverts commit 12178b1aa0da3c29434e95a2a0126cf3ef5706a7.

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

* Support multiimage masking

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

* refactor transformers 2d into multiple legacy variants.

* fix: init.

* fix recursive init.

* add inits.

* make transformer block creation more modular.

* complete refactor.

* remove forward

* debug

* remove legacy blocks and refactor within the module itself.

* remove print

* guard caption projection

* remove fetcher.

* reduce the number of args.

* fix: norm_type

* group variables that are shared.

* remove _get_transformer_blocks

* harmonize the init function signatures.

* transformer_blocks to common

* repeat .

* add: utility to format our docs too 📜

* debugging saga

* fix: message

* checking

* should be fixed.

* revert pipeline_fixture

* remove empty line

* make style

* fix: setup.py

* style.

* remove class assignments for linear and conv.

* fix: self.nn

* add from_pipe



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

* Fix SVD bug (shape of `time_context`)

* Formatting code

* Formatting src/diffusers/models/transformers/transformer_temporal.py by `make style && make quality`

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Co-authored-by: kevinkhwu <kevinkhwu@tencent.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* 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`

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

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

* cleanse and refactor lora testing suite.

* more cleanup.

* make check_if_lora_correctly_set a utility function

* fix: typo

* retrigger ci

* style

update

* Change path to posix

* running isort

* run style and quality checks

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

* Fix ControlNetModel.from_unet do not load add_embedding

* delete white space in blank line

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

* debugging

* let's see the numbers

* let's see the numbers

* let's see the numbers

* restrict tolerance.

* increase inference steps.

* shallow copy of cross_attentionkwargs

* remove print

* Correction for non-integral image resolutions with quantizations other than float32.

* Support for training, and use of diffusers-style casting.

* pop scale from the top-level unet instead of getting it.

* improve readability.

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

* fix a little bit.

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

* Fix PyTorch's convention for inplace functions

* Fix import structure in __init__.py and update config loading logic in test_config.py

* Update configuration access

* Fix typos

* Trim trailing white spaces

* Fix typo in logger name

* Revert "Fix PyTorch's convention for inplace functions"

This reverts commit f65dc4afcb57ceb43d5d06389229d47bafb10d2d.

* Fix typo in step_index property description

* Revert "Update configuration access"

This reverts commit 8d44e870b8c1ad08802e3e904c34baeca1b598f8.

* Revert "Fix import structure in __init__.py and update config loading logic in test_config.py"

This reverts commit 2ad5e8bca25aede3b912da22bd57285b598fe171.

* Fix typos

* Fix typos

* Fix typos

* Fix a typo: tranform -> transform

* Add properties and `IPAdapterTesterMixin` tests for `StableDiffusionPanoramaPipeline`

* Fix variable name typo and update comments

* Update deprecated `output_type="numpy"` to "np" in test files

* Discard changes to src/diffusers/pipelines/stable_diffusion_panorama/pipeline_stable_diffusion_panorama.py

* Update test_stable_diffusion_panorama.py

* Update numbers in README.md

* Update get_guidance_scale_embedding method to use timesteps instead of w

* Update number of checkpoints in README.md

* Add type hints and fix var name

* Fix PyTorch's convention for inplace functions

* Fix a typo

* Revert "Fix PyTorch's convention for inplace functions"

This reverts commit 74350cf65b2c9aa77f08bec7937d7a8b13edb509.

* Fix typos

* Indent

* Refactor get_guidance_scale_embedding method in LEditsPPPipelineStableDiffusionXL class

* fix typo in UNet2DConditionModel documentation

* Fix indentation that may fix doc rendering

* Fix squished doc lines

* update

* update

* update

* update

* update

* update

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