GitLab

* Fix typos in docs and comments

* Apply style fixes

---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

* [tests] Add torch.compile() test for WanTransformer3DModel

* fix wan recompilation issues.

* style

---------
Co-authored-by: tongyu0924 <winnie920924@gmail.com>

udpate

up

update

* initial commit

* initial commit

* initial commit

* initial commit

* initial commit

* initial commit

* Update examples/dreambooth/train_dreambooth_lora_hidream.py
Co-authored-by: Bagheera <59658056+bghira@users.noreply.github.com>

* move prompt embeds, pooled embeds outside

* Update examples/dreambooth/train_dreambooth_lora_hidream.py
Co-authored-by: hlky <hlky@hlky.ac>

* Update examples/dreambooth/train_dreambooth_lora_hidream.py
Co-authored-by: hlky <hlky@hlky.ac>

* fix import

* fix import and tokenizer 4, text encoder 4 loading

* te

* prompt embeds

* fix naming

* shapes

* initial commit to add HiDreamImageLoraLoaderMixin

* fix init

* add tests

* loader

* fix model input

* add code example to readme

* fix default max length of text encoders

* prints

* nullify training cond in unpatchify for temp fix to incompatible shaping of transformer output during training

* smol fix

* unpatchify

* unpatchify

* fix validation

* flip pred and loss

* fix shift!!!

* revert unpatchify changes (for now)

* smol fix

* Apply style fixes

* workaround moe training

* workaround moe training

* remove prints

* to reduce some memory, keep vae in `weight_dtype` same as we have for flux (as it's the same vae)
https://github.com/huggingface/diffusers/blob/bbd0c161b55ba2234304f1e6325832dd69c60565/examples/dreambooth/train_dreambooth_lora_flux.py#L1207



* refactor to align with HiDream refactor

* refactor to align with HiDream refactor

* refactor to align with HiDream refactor

* add support for cpu offloading of text encoders

* Apply style fixes

* adjust lr and rank for train example

* fix copies

* Apply style fixes

* update README

* update README

* update README

* fix license

* keep prompt2,3,4 as None in validation

* remove reverse ode comment

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

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

* vae offload change

* fix text encoder offloading

* Apply style fixes

* cleaner to_kwargs

* fix module name in copied from

* add requirements

* fix offloading

* fix offloading

* fix offloading

* update transformers version in reqs

* try AutoTokenizer

* try AutoTokenizer

* Apply style fixes

* empty commit

* Delete tests/lora/test_lora_layers_hidream.py

* change tokenizer_4 to load with AutoTokenizer as well

* make text_encoder_four and tokenizer_four configurable

* save model card

* save model card

* revert T5

* fix test

* remove non diffusers lumina2 conversion

---------
Co-authored-by: Bagheera <59658056+bghira@users.noreply.github.com>
Co-authored-by: hlky <hlky@hlky.ac>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
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[cogview4][feat] Support attention mechanism with variable-length support and batch packing (#11349)

* [cogview4] Enhance attention mechanism with variable-length support and batch packing

---------
Co-authored-by: YiYi Xu <yixu310@gmail.com>
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

up

* update transformer

---------
Co-authored-by: Aryan <aryan@huggingface.co>

* add

* Update pe_selection_index_based_on_dim

* Make pe_selection_index_based_on_dim work with torh.compile

* Fix AuraFlowTransformer2DModel's dpcstring default values

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

* Add AuraFlowLoraLoaderMixin

* Add comments, remove qkv fusion

* Add Tests

* Add AuraFlowLoraLoaderMixin to documentation

* Add Suggested changes

* Change attention_kwargs->joint_attention_kwargs

* Rebasing derp.

* fix

* fix

* Quality fixes.

* make style

* `make fix-copies`

* `ruff check --fix`

* Attept 1 to fix tests.

* Attept 2 to fix tests.

* Attept 3 to fix tests.

* Address review comments.

* Rebasing derp.

* Get more tests passing by copying from Flux. Address review comments.

* `joint_attention_kwargs`->`attention_kwargs`

* Add `lora_scale` property for te LoRAs.

* Make test better.

* Remove useless property.

* Skip TE-only tests for AuraFlow.

* Support LoRA for non-CLIP TEs.

* Restore LoRA tests.

* Undo adding LoRA support for non-CLIP TEs.

* Undo support for TE in AuraFlow LoRA.

* `make fix-copies`

* Sync with upstream changes.

* Remove unneeded stuff.

* Mirror `Lumina2`.

* Skip for MPS.

* Address review comments.

* Remove duplicated code.

* Remove unnecessary code.

* Remove repeated docs.

* Propagate attention.

* Fix TE target modules.

* MPS fix for LoRA tests.

* Unrelated TE LoRA tests fix.

* Fix AuraFlow LoRA tests by applying to the right denoiser layers.
Co-authored-by: AstraliteHeart <81396681+AstraliteHeart@users.noreply.github.com>

* Apply style fixes

* empty commit

* Fix the repo consistency issues.

* Remove unrelated changes.

* Style.

* Fix `test_lora_fuse_nan`.

* fix quality issues.

* `pytest.xfail` -> `ValueError`.

* Add back `skip_mps`.

* Apply style fixes

* `make fix-copies`

---------
Co-authored-by: Warlord-K <warlordk28@gmail.com>
Co-authored-by: hlky <hlky@hlky.ac>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: AstraliteHeart <81396681+AstraliteHeart@users.noreply.github.com>
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

* added controlnet for sana transformer

* improve code quality

* addressed PR comments

* bug fixes

* added test cases

* update

* added dummy objects

* addressed PR comments

* update

* Forcing update

* add to docs

* code quality

* addressed PR comments

* addressed PR comments

* update

* addressed PR comments

* added proper styling

* update

* Revert "added proper styling"

This reverts commit 344ee8a7014ada095b295034ef84341f03b0e359.

* manually ordered

* Apply suggestions from code review

---------
Co-authored-by: Aryan <contact.aryanvs@gmail.com>

* HiDream Image

* update

* -einops

* py3.8

* fix -einops

* mixins, offload_seq, option_components

* docs

* Apply style fixes

* trigger tests

* Apply suggestions from code review
Co-authored-by: Aryan <contact.aryanvs@gmail.com>

* joint_attention_kwargs -> attention_kwargs, fixes

* fast tests

* -_init_weights

* style tests

* move reshape logic

* update slice 😴

* supports_dduf

* 🤷🏻

‍♂️

* Update src/diffusers/models/transformers/transformer_hidream_image.py
Co-authored-by: Aryan <contact.aryanvs@gmail.com>

* address review comments

* update tests

* doc updates

* update

* Update src/diffusers/models/transformers/transformer_hidream_image.py

* Apply style fixes

---------
Co-authored-by: hlky <hlky@hlky.ac>
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

* HiDream Image


---------
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: Aryan <contact.aryanvs@gmail.com>
Co-authored-by: Aryan <aryan@huggingface.co>

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* add tests

* update docs

* raise value error

* warning for true cfg and guidance scale

* fix test

* add sana-sprint




---------
Co-authored-by: Junsong Chen <cjs1020440147@icloud.com>
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Aryan <aryan@huggingface.co>

* update


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

* cogview4 control training


---------
Co-authored-by: OleehyO <leehy0357@gmail.com>
Co-authored-by: yiyixuxu <yixu310@gmail.com>

Ensure that hidden_state and shift/scale are on the same device when running with multiple GPUs

Co-authored-by: Jimmy <39@🇺🇸.com>

* update

* make fix-copies

* update

* added support for from_single_file

* added diffusers mapping script

* added testcase

* bug fix

* updated tests

* corrected code quality

* corrected code quality

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

* update

* update

* update

* update

* update

* update

* update

* Fix Graph Breaks When Compiling CogView4

Eliminate this:

```
t]V0304 10:24:23.421000 3131076 torch/_dynamo/guards.py:2813] [0/4] [__recompiles] Recompiling function forward in /home/zeyi/repos/diffusers/src/diffusers/models/transformers/transformer_cogview4.py:374
V0304 10:24:23.421000 3131076 torch/_dynamo/guards.py:2813] [0/4] [__recompiles]     triggered by the following guard failure(s):
V0304 10:24:23.421000 3131076 torch/_dynamo/guards.py:2813] [0/4] [__recompiles]     - 0/3: ___check_obj_id(L['self'].rope.freqs_h, 139976127328032)    
V0304 10:24:23.421000 3131076 torch/_dynamo/guards.py:2813] [0/4] [__recompiles]     - 0/2: ___check_obj_id(L['self'].rope.freqs_h, 139976107780960)    
V0304 10:24:23.421000 3131076 torch/_dynamo/guards.py:2813] [0/4] [__recompiles]     - 0/1: ___check_obj_id(L['self'].rope.freqs_h, 140022511848960)    
V0304 10:24:23.421000 3131076 torch/_dynamo/guards.py:2813] [0/4] [__recompiles]     - 0/0: ___check_obj_id(L['self'].rope.freqs_h, 140024081342416)   
```

* Update transformer_cogview4.py

* fix cogview4 rotary pos embed

* Apply style fixes

---------
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* update

* update

* update

* add tests

* update

* add model tests

* update docs

* update

* update example

* fix defaults

* update

* update

* refactor image-to-video pipeline

* update

* fix copied from

* use FP32LayerNorm

* Update EasyAnimate V5.1

* Add docs && add tests && Fix comments problems in transformer3d and vae

* delete comments and remove useless import

* delete process

* Update EXAMPLE_DOC_STRING

* rename transformer file

* make fix-copies

* make style

* refactor pt. 1

* update toctree.yml

* add model tests

* Update layer_norm for norm_added_q and norm_added_k in Attention

* Fix processor problem

* refactor vae

* Fix problem in comments

* refactor tiling; remove einops dependency

* fix docs path

* make fix-copies

* Update src/diffusers/pipelines/easyanimate/pipeline_easyanimate_control.py

* update _toctree.yml

* fix test

* update

* update

* update

* make fix-copies

* fix tests

---------
Co-authored-by: Aryan <aryan@huggingface.co>
Co-authored-by: Aryan <contact.aryanvs@gmail.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* Add wanx pipeline, model and example

* wanx_merged_v1

* change WanX into Wan

* fix i2v fp32 oom error

Link: https://code.alibaba-inc.com/open_wanx2/diffusers/codereview/20607813



* support t2v load fp32 ckpt

* add example

* final merge v1

* Update autoencoder_kl_wan.py

* up

* update middle, test up_block

* up up

* one less nn.sequential

* up more

* up

* more

* [refactor] [wip] Wan transformer/pipeline (#10926)

* update

* update

* refactor rope

* refactor pipeline

* make fix-copies

* add transformer test

* update

* update

* make style

* update tests

* tests

* conversion script

* conversion script

* update

* docs

* remove unused code

* fix _toctree.yml

* update dtype

* fix test

* fix tests: scale

* up

* more

* Apply suggestions from code review

* Apply suggestions from code review

* style

* Update scripts/convert_wan_to_diffusers.py

* update docs

* fix

---------
Co-authored-by: Yitong Huang <huangyitong.hyt@alibaba-inc.com>
Co-authored-by: 亚森 <wangjiayu.wjy@alibaba-inc.com>
Co-authored-by: Aryan <aryan@huggingface.co>

* update

* apply review suggestions

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

* update

* update

* update

* feat: lora support for Lumina2.

* fix-copies.

* updates

* updates

* docs.

* fix

* add: training script.

* tests

* updates

* updates

* major updates.

* updates

* fixes

* docs.

* updates

* updates

* first draft model loading refactor

* revert name change

* fix bnb

* revert name

* fix dduf

* fix huanyan

* style

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

* suggestions from reviews

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

* remove safetensors check

* fix default value

* more fix from suggestions

* revert logic for single file

* style

* typing + fix couple of issues

* improve speed

* Update src/diffusers/models/modeling_utils.py
Co-authored-by: Aryan <aryan@huggingface.co>

* fp8 dtype

* add tests

* rename resolved_archive_file to resolved_model_file

* format

* map_location default cpu

* add utility function

* switch to smaller model + test inference

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

* rm comment

* add log

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

* add decorator

* cosine sim instead

* fix use_keep_in_fp32_modules

* comm

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

* init

* encode with glm

* draft schedule

* feat(scheduler): Add CogView scheduler implementation

* feat(embeddings): add CogView 2D rotary positional embedding

* 1

* Update pipeline_cogview4.py

* fix the timestep init and sigma

* update latent

* draft patch(not work)

* fix

* [WIP][cogview4]: implement initial CogView4 pipeline

Implement the basic CogView4 pipeline structure with the following changes:
- Add CogView4 pipeline implementation
- Implement DDIM scheduler for CogView4
- Add CogView3Plus transformer architecture
- Update embedding models

Current limitations:
- CFG implementation uses padding for sequence length alignment
- Need to verify transformer inference alignment with Megatron

TODO:
- Consider separate forward passes for condition/uncondition
  instead of padding approach

* [WIP][cogview4][refactor]: Split condition/uncondition forward pass in CogView4 pipeline

Split the forward pass for conditional and unconditional predictions in the CogView4 pipeline to match the original implementation. The noise prediction is now done separately for each case before combining them for guidance. However, the results still need improvement.

This is a work in progress as the generated images are not yet matching expected quality.

* use with -2 hidden state

* remove text_projector

* 1

* [WIP] Add tensor-reload to align input from transformer block

* [WIP] for older glm

* use with cogview4 transformers forward twice of u and uc

* Update convert_cogview4_to_diffusers.py

* remove this

* use main example

* change back

* reset

* setback

* back

* back 4

* Fix qkv conversion logic for CogView4 to Diffusers format

* back5

* revert to sat to cogview4 version

* update a new convert from megatron

* [WIP][cogview4]: implement CogView4 attention processor

Add CogView4AttnProcessor class for implementing scaled dot-product attention
with rotary embeddings for the CogVideoX model. This processor concatenates
encoder and hidden states, applies QKV projections and RoPE, but does not
include spatial normalization.

TODO:
- Fix incorrect QKV projection weights
- Resolve ~25% error in RoPE implementation compared to Megatron

* [cogview4] implement CogView4 transformer block

Implement CogView4 transformer block following the Megatron architecture:
- Add multi-modulate and multi-gate mechanisms for adaptive layer normalization
- Implement dual-stream attention with encoder-decoder structure
- Add feed-forward network with GELU activation
- Support rotary position embeddings for image tokens

The implementation follows the original CogView4 architecture while adapting
it to work within the diffusers framework.

* with new attn

* [bugfix] fix dimension mismatch in CogView4 attention

* [cogview4][WIP]: update final normalization in CogView4 transformer

Refactored the final normalization layer in CogView4 transformer to use separate layernorm and AdaLN operations instead of combined AdaLayerNormContinuous. This matches the original implementation but needs validation.

Needs verification against reference implementation.

* 1

* put back

* Update transformer_cogview4.py

* change time_shift

* Update pipeline_cogview4.py

* change timesteps

* fix

* change text_encoder_id

* [cogview4][rope] align RoPE implementation with Megatron

- Implement apply_rope method in attention processor to match Megatron's implementation
- Update position embeddings to ensure compatibility with Megatron-style rotary embeddings
- Ensure consistent rotary position encoding across attention layers

This change improves compatibility with Megatron-based models and provides
better alignment with the original implementation's positional encoding approach.

* [cogview4][bugfix] apply silu activation to time embeddings in CogView4

Applied silu activation to time embeddings before splitting into conditional
and unconditional parts in CogView4Transformer2DModel. This matches the
original implementation and helps ensure correct time conditioning behavior.

* [cogview4][chore] clean up pipeline code

- Remove commented out code and debug statements
- Remove unused retrieve_timesteps function
- Clean up code formatting and documentation

This commit focuses on code cleanup in the CogView4 pipeline implementation, removing unnecessary commented code and improving readability without changing functionality.

* [cogview4][scheduler] Implement CogView4 scheduler and pipeline

* now It work

* add timestep

* batch

* change convert scipt

* refactor pt. 1; make style

* refactor pt. 2

* refactor pt. 3

* add tests

* make fix-copies

* update toctree.yml

* use flow match scheduler instead of custom

* remove scheduling_cogview.py

* add tiktoken to test dependencies

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

* apply suggestions from review

* use diffusers apply_rotary_emb

* update flow match scheduler to accept timesteps

* fix comment

* apply review sugestions

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

---------
Co-authored-by: 三洋三洋 <1258009915@qq.com>
Co-authored-by: OleehyO <leehy0357@gmail.com>
Co-authored-by: Aryan <aryan@huggingface.co>
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* up