GitLab

* update

* update

* update

* update

* AutoModel

* ...

* lol

* ...

* add test

* update

* make fix-copies

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* implement record_stream for better performance.

* fix

* style.

* merge #11097

* Update src/diffusers/hooks/group_offloading.py
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* fixes

* docstring.

* remaining todos in low_cpu_mem_usage

* tests

* updates to docs.

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* Add missing 'gradient_checkpointing = False' attr

* Add (limited) tests for Mochi autoencoder

* Apply style fixes

* pass 'conv_cache' as arg instead of kwarg

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* update

* update

* update

* allow models to run with a user-provided dtype map instead of a single dtype

* make style

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* make style

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* handle shared tensors

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* rewrite memory count without implicitly using dimensions by @ic-synth

* replace F.pad by built-in padding in Conv3D

* in-place sums to reduce memory allocations

* fixed trailing whitespace

* file reformatted

* in-place sums

* simpler in-place expressions

* removed in-place sum, may affect backward propagation logic

* removed in-place sum, may affect backward propagation logic

* removed in-place sum, may affect backward propagation logic

* reverted change

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* add tests

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* raise value error

* warning for true cfg and guidance scale

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* Don't use `torch_dtype` when `quantization_config` is set

* up

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* Apply suggestions from code review

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* add sana-sprint




---------
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* init

* update

* update

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* apply_faster_cache -> apply_fastercache

* fix

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---------
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up

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* clean up

Modify UNet's ResNet implementation to resolve stride mismatch in Torch's DDP

* update


---------
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* cogview4 control training


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reverts accidental change that removes attn_mask in attn. Improves flux ptxla by using flash block sizes. Moves encoding outside the for loop.
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* get_1d_rotary_pos_embed support npu

* Update src/diffusers/models/embeddings.py

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

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* update

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* added support for from_single_file

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---------
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* update

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* Update docs/source/en/quantization/quanto.md
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* Update src/diffusers/quantizers/quanto/utils.py
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* update

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* update

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* update

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* update

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* 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

---------
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* update

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* update

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* refactor image-to-video pipeline

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* 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

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* 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

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* make fix-copies

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---------
Co-authored-by: Aryan <aryan@huggingface.co>
Co-authored-by: Aryan <contact.aryanvs@gmail.com>
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* 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

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* up up

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* up more

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

* update

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* refactor rope

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* conversion script

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* update

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* fix _toctree.yml

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* fix tests: scale

* up

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* Apply suggestions from code review

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* style

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* 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>

* ControlNet Union scale

* fix

* universal interface

* from_multi

* from_multi

* Initial implementation of Flux multi IP-Adapter

* Update src/diffusers/pipelines/flux/pipeline_flux.py
Co-authored-by: hlky <hlky@hlky.ac>

* Update src/diffusers/pipelines/flux/pipeline_flux.py
Co-authored-by: hlky <hlky@hlky.ac>

* Changes for ipa image embeds

* Update src/diffusers/pipelines/flux/pipeline_flux.py
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* Update src/diffusers/pipelines/flux/pipeline_flux.py
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* make style && make quality

* Updated ip_adapter test

* Created typing_utils.py

---------
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* update

* apply review suggestions

---------
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* update

* update

* update

correct qk norm list.

* Fix `torch_dtype` in Kolors text encoder with `transformers` v4.49

* Default torch_dtype and warning