GitLab

[Bug fix] "previous_timestep()" in DDPM scheduling compatible with "trailing" and "linspace" options (#9384)

* Update scheduling_ddpm.py

* fix copies

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

* Fix wrong output on 3n-1 steps count

* Add sde handling to 3 order

* make

* copies

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Co-authored-by: hlky <hlky@hlky.ac>

Add beta, exponential and karras sigmas to FlowMatchEuler

* Fix beta and exponential sigmas + add tests

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

* update

* udpate

* update transformer

* make style

* fix

* add conversion script

* update

* fix

* update

* fix

* update

* fixes

* make style

* update

* update

* update

* init

* update

* update

* add

* up

* up

* up

* update

* mochi transformer

* remove original implementation

* make style

* update inits

* update conversion script

* docs

* Update src/diffusers/pipelines/mochi/pipeline_mochi.py
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* Update src/diffusers/pipelines/mochi/pipeline_mochi.py
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* fix docs

* pipeline fixes

* make style

* invert sigmas in scheduler; fix pipeline

* fix pipeline num_frames

* flip proj and gate in swiglu

* make style

* fix

* make style

* fix tests

* latent mean and std fix

* update

* cherry-pick 1069d210e1b9e84a366cdc7a13965626ea258178

* remove additional sigma already handled by flow match scheduler

* fix

* remove hardcoded value

* replace conv1x1 with linear

* Update src/diffusers/pipelines/mochi/pipeline_mochi.py
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

* framewise decoding and conv_cache

* make style

* Apply suggestions from code review

* mochi vae encoder changes

* rebase correctly

* Update scripts/convert_mochi_to_diffusers.py

* fix tests

* fixes

* make style

* update

* make style

* update

* add framewise and tiled encoding

* make style

* make original vae implementation behaviour the default; note: framewise encoding does not work

* remove framewise encoding implementation due to presence of attn layers

* fight test 1

* fight test 2

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

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

* Slight performance improvement to Euler

* Slight performance improvement to EDMEuler

* Slight performance improvement to FlowMatchHeun

* Slight performance improvement to KDPM2Ancestral

* Update KDPM2AncestralDiscreteSchedulerTest

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

Refactor SchedulerOutput and add pred_original_sample in `DPMSolverSDE`, `Heun`, `KDPM2Ancestral` and `KDPM2` (#9650)

Refactor SchedulerOutput and add pred_original_sample
Co-authored-by: YiYi Xu <yixu310@gmail.com>

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

Add beta sigmas / beta noise schedule

* exponential sigmas

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

* make style

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

migrate the BrownianTree to BrownianInterval
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* add CogVideoX

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Co-authored-by: Aryan <aryan@huggingface.co>
Co-authored-by: sayakpaul <spsayakpaul@gmail.com>
Co-authored-by: Aryan <contact.aryanvs@gmail.com>
Co-authored-by: yiyixuxu <yixu310@gmail.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

add flux!
Signed-off-by: Adrien <adrien@huggingface.co>
Co-authored-by: Adrien <adrien.69740@gmail.com>
Co-authored-by: Anatoly Belikov <abelikov@singularitynet.io>
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
Co-authored-by: yiyixuxu <yixu310@gmail.com>

* WIP modeling code and pipeline

* add custom attention processor + custom activation + add to init

* correct ProjectionModel forward

* add stable audio to __initèè

* add autoencoder and update pipeline and modeling code

* add half Rope

* add partial rotary v2

* add temporary modfis to scheduler

* add EDM DPM Solver

* remove TODOs

* clean GLU

* remove att.group_norm to attn processor

* revert back src/diffusers/schedulers/scheduling_dpmsolver_multistep.py

* refactor GLU -> SwiGLU

* remove redundant args

* add channel multiples in autoencoder docstrings

* changes in docsrtings and copyright headers

* clean pipeline

* further cleaning

* remove peft and lora and fromoriginalmodel

* Delete src/diffusers/pipelines/stable_audio/diffusers.code-workspace

* make style

* dummy models

* fix copied from

* add fast oobleck tests

* add brownian tree

* oobleck autoencoder slow tests

* remove TODO

* fast stable audio pipeline tests

* add slow tests

* make style

* add first version of docs

* wrap is_torchsde_available to the scheduler

* fix slow test

* test with input waveform

* add input waveform

* remove some todos

* create stableaudio gaussian projection + make style

* add pipeline to toctree

* fix copied from

* make quality

* refactor timestep_features->time_proj

* refactor joint_attention_kwargs->cross_attention_kwargs

* remove forward_chunk

* move StableAudioDitModel to transformers folder

* correct convert + remove partial rotary embed

* apply suggestions from yiyixuxu -> removing attn.kv_heads

* remove temb

* remove cross_attention_kwargs

* further removal of cross_attention_kwargs

* remove text encoder autocast to fp16

* continue removing autocast

* make style

* refactor how text and audio are embedded

* add paper

* update example code

* make style

* unify projection model forward + fix device placement

* make style

* remove fuse qkv

* apply suggestions from review

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

* make style

* smaller models in fast tests

* pass sequential offloading fast tests

* add docs for vae and autoencoder

* make style and update example

* remove useless import

* add cosine scheduler

* dummy classes

* cosine scheduler docs

* better description of scheduler

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

* remove resume_download

* fix: _fetch_index_file call.

* remove resume_download from docs.

* Add the SDE variant of DPM-Solver and DPM-Solver++ to DPM Single Step


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Co-authored-by: cmdr2 <secondary.cmdr2@gmail.com>

* add lavender flow transformer

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

* Fix static typing and doc typos

* Fix more same type hint typos with make fix-copies

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Co-authored-by: zhuole1025 <zhuole1025@gmail.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* initial fix

* apply suggestion

* delete step_index line

Update scheduling_flow_match_euler_discrete.py

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

* up

* add sd3

* update

* update

* add tests

* fix copies

* fix docs

* update

* add dreambooth lora

* add LoRA

* update

* update

* update

* update

* import fix

* update

* Update src/diffusers/pipelines/stable_diffusion_3/pipeline_stable_diffusion_3.py
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* import fix 2

* update

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

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

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

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

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

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

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

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

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

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

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

* update

* update

* update

* fix ckpt id

* fix more ids

* update

* missing doc

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

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

* Update docs/source/en/api/pipelines/stable_diffusion/stable_diffusion_3.md
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Update docs/source/en/api/pipelines/stable_diffusion/stable_diffusion_3.md
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* update'

* fix

* update

* Update src/diffusers/models/autoencoders/autoencoder_kl.py

* Update src/diffusers/models/autoencoders/autoencoder_kl.py

* note on gated access.

* requirements

* licensing

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

* fix: euledm when using the exp sigma schedule.

* fix-copies

* remove print.

* reduce friction

* yiyi's suggestioms

* Fix copying mechanism typos

* fix copying mecha

* Revert, since they are in TODO

* Fix copying mechanism

Fix grammatical error

* 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>

* 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

* support custom sigmas and timesteps, dpm euler

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Benjamin Bossan <BenjaminBossan@users.noreply.github.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

Fix imports

`model_output.shape` may only have rank 1.

There are warnings related to use of random keys.

```
tests/schedulers/test_scheduler_flax.py: 13 warnings
  /Users/phillypham/diffusers/src/diffusers/schedulers/scheduling_ddpm_flax.py:268: FutureWarning: normal accepts a single key, but was given a key array of shape (1, 2) != (). Use jax.vmap for batching. In a future JAX version, this will be an error.
    noise = jax.random.normal(split_key, shape=model_output.shape, dtype=self.dtype)

tests/schedulers/test_scheduler_flax.py::FlaxDDPMSchedulerTest::test_betas
  /Users/phillypham/virtualenv/diffusers/lib/python3.9/site-packages/jax/_src/random.py:731: FutureWarning: uniform accepts a single key, but was given a key array of shape (1,) != (). Use jax.vmap for batching. In a future JAX version, this will be an error.
    u = uniform(key, shape, dtype, lo, hi)  # type: ignore[arg-type]
```

* Deprecate resume_download

* align docstring with transformers

* style

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

* Added get_velocity function to EulerDiscreteScheduler.

* Fix white space on blank lines

* Added copied from statement

* back to the original.

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Co-authored-by: Ruining Li <ruining@robots.ox.ac.uk>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* introduce sigma schedule.
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* address yiyi

* update docstrings.

* implement the schedule for EDMDPMSolverMultistepScheduler

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Co-authored-by: Suraj Patil <surajp815@gmail.com>

* UniPC Multistep add `rescale_betas_zero_snr`

Same patch as DPM and Euler with the patched final alpha cumprod

BF16 doesn't seem to break down, I think cause UniPC upcasts during some
phases already? We could still force an upcast since it only
loses ≈ 0.005 it/s for me but the difference in output is very small. A
better endeavor might upcasting in step() and removing all the other
upcasts elsewhere?

* UniPC ZSNR UT

* Re-add `rescale_betas_zsnr` doc oops

* UniPC UTs iterate solvers on FP16

It wasn't catching errs on order==3. Might be excessive?

* UniPC Multistep fix tensor dtype/device on order=3

* UniPC UTs Add v_pred to fp16 test iter

For completions sake. Probably overkill?