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  1. 04 Nov, 2022 1 commit
  3. 03 Nov, 2022 5 commits
    • Patrick von Platen's avatar
      Correct VQDiffusion Pipeline import · 33108bfa
      Patrick von Platen authored
      33108bfa
    • anton-l's avatar
      Release: v0.7.0 · 1578679f
      anton-l authored
      1578679f
    • Suraj Patil's avatar
      default fast model loading 🔥 (#1115) · 74821781
      Suraj Patil authored 
      

* make accelerate hard dep

* default fast init

* move params to cpu when device map is None

* handle device_map=None

* handle torch < 1.9

* remove device_map="auto"

* style

* add accelerate in torch extra

* remove accelerate from extras["test"]

* raise an error if torch is available but not accelerate

* update installation docs

* Apply suggestions from code review
Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>

* improve defautl loading speed even further, allow disabling fats loading

* address review comments

* adapt the tests

* fix test_stable_diffusion_fast_load

* fix test_read_init

* temp fix for dummy checks

* Trigger Build

* Apply suggestions from code review
Co-authored-by: default avatarAnton Lozhkov <anton@huggingface.co>
Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: default avatarAnton Lozhkov <anton@huggingface.co>
      74821781
    • Will Berman's avatar
      VQ-diffusion (#658) · ef2ea33c
      Will Berman authored 
      

* Changes for VQ-diffusion VQVAE

Add specify dimension of embeddings to VQModel:
`VQModel` will by default set the dimension of embeddings to the number
of latent channels. The VQ-diffusion VQVAE has a smaller
embedding dimension, 128, than number of latent channels, 256.

Add AttnDownEncoderBlock2D and AttnUpDecoderBlock2D to the up and down
unet block helpers. VQ-diffusion's VQVAE uses those two block types.

* Changes for VQ-diffusion transformer

Modify attention.py so SpatialTransformer can be used for
VQ-diffusion's transformer.

SpatialTransformer:
- Can now operate over discrete inputs (classes of vector embeddings) as well as continuous.
- `in_channels` was made optional in the constructor so two locations where it was passed as a positional arg were moved to kwargs
- modified forward pass to take optional timestep embeddings

ImagePositionalEmbeddings:
- added to provide positional embeddings to discrete inputs for latent pixels

BasicTransformerBlock:
- norm layers were made configurable so that the VQ-diffusion could use AdaLayerNorm with timestep embeddings
- modified forward pass to take optional timestep embeddings

CrossAttention:
- now may optionally take a bias parameter for its query, key, and value linear layers

FeedForward:
- Internal layers are now configurable

ApproximateGELU:
- Activation function in VQ-diffusion's feedforward layer

AdaLayerNorm:
- Norm layer modified to incorporate timestep embeddings

* Add VQ-diffusion scheduler

* Add VQ-diffusion pipeline

* Add VQ-diffusion convert script to diffusers

* Add VQ-diffusion dummy objects

* Add VQ-diffusion markdown docs

* Add VQ-diffusion tests

* some renaming

* some fixes

* more renaming

* correct

* fix typo

* correct weights

* finalize

* fix tests

* Apply suggestions from code review
Co-authored-by: default avatarAnton Lozhkov <aglozhkov@gmail.com>

* Apply suggestions from code review
Co-authored-by: default avatarPedro Cuenca <pedro@huggingface.co>

* finish

* finish

* up
Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: default avatarAnton Lozhkov <aglozhkov@gmail.com>
Co-authored-by: default avatarPedro Cuenca <pedro@huggingface.co>
      ef2ea33c
    • Revist's avatar
      feat: add repaint (#974) · d38c8043
      Revist authored 
      

* feat: add repaint

* fix: fix quality check with `make fix-copies`

* fix: remove old unnecessary arg

* chore: change default to DDPM (looks better in experiments)

* ".to(device)" changed to "device="
Co-authored-by: default avatarAnton Lozhkov <aglozhkov@gmail.com>

* make generator device-specific
Co-authored-by: default avatarAnton Lozhkov <aglozhkov@gmail.com>

* make generator device-specific and change shape
Co-authored-by: default avatarAnton Lozhkov <aglozhkov@gmail.com>

* fix: add preprocessing for image and mask
Co-authored-by: default avatarAnton Lozhkov <aglozhkov@gmail.com>

* fix: update test
Co-authored-by: default avatarAnton Lozhkov <aglozhkov@gmail.com>

* Update src/diffusers/pipelines/repaint/pipeline_repaint.py
Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>

* Add docs and examples

* Fix toctree
Co-authored-by: default avatarfja <fja@zurich.ibm.com>
Co-authored-by: default avatarAnton Lozhkov <aglozhkov@gmail.com>
Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: default avatarAnton Lozhkov <anton@huggingface.co>
      d38c8043
  5. 31 Oct, 2022 1 commit
  7. 25 Oct, 2022 1 commit
  9. 20 Oct, 2022 1 commit
  11. 19 Oct, 2022 2 commits
  13. 18 Oct, 2022 2 commits
  15. 14 Oct, 2022 1 commit
  17. 13 Oct, 2022 2 commits
  19. 07 Oct, 2022 2 commits
  21. 06 Oct, 2022 6 commits
  23. 03 Oct, 2022 1 commit
    • Pedro Cuenca's avatar
      Fix import with Flax but without PyTorch (#688) · 688031c5
      Pedro Cuenca authored 
      * Don't use `load_state_dict` if torch is not installed.

* Define `SchedulerOutput` to use torch or flax arrays.

* Don't import LMSDiscreteScheduler without torch.

* Create distinct FlaxSchedulerOutput.

* Additional changes required for FlaxSchedulerMixin

* Do not import torch pipelines in Flax.

* Revert "Define `SchedulerOutput` to use torch or flax arrays."

This reverts commit f653140134b74d9ffec46d970eb46925fe3a409d.

* Prefix Flax scheduler outputs for consistency.

* make style

* FlaxSchedulerOutput is now a dataclass.

* Don't use f-string without placeholders.

* Add blank line.

* Style (docstrings)
      688031c5
  25. 20 Sep, 2022 1 commit
  27. 19 Sep, 2022 1 commit
  29. 15 Sep, 2022 2 commits
    • Pedro Cuenca's avatar
      UNet Flax with FlaxModelMixin (#502) · d8b0e4f4
      Pedro Cuenca authored 
      

* First UNet Flax modeling blocks.

Mimic the structure of the PyTorch files.
The model classes themselves need work, depending on what we do about
configuration and initialization.

* Remove FlaxUNet2DConfig class.

* ignore_for_config non-config args.

* Implement `FlaxModelMixin`

* Use new mixins for Flax UNet.

For some reason the configuration is not correctly applied; the
signature of the `__init__` method does not contain all the parameters
by the time it's inspected in `extract_init_dict`.

* Import `FlaxUNet2DConditionModel` if flax is available.

* Rm unused method `framework`

* Update src/diffusers/modeling_flax_utils.py
Co-authored-by: default avatarSuraj Patil <surajp815@gmail.com>

* Indicate types in flax.struct.dataclass as pointed out by @mishig25
Co-authored-by: default avatarMishig Davaadorj <mishig.davaadorj@coloradocollege.edu>

* Fix typo in transformer block.

* make style

* some more changes

* make style

* Add comment

* Update src/diffusers/modeling_flax_utils.py
Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>

* Rm unneeded comment

* Update docstrings

* correct ignore kwargs

* make style

* Update docstring examples

* Make style

* Style: remove empty line.

* Apply style (after upgrading black from pinned version)

* Remove some commented code and unused imports.

* Add init_weights (not yet in use until #513).

* Trickle down deterministic to blocks.

* Rename q, k, v according to the latest PyTorch version.

Note that weights were exported with the old names, so we need to be
careful.

* Flax UNet docstrings, default props as in PyTorch.

* Fix minor typos in PyTorch docstrings.

* Use FlaxUNet2DConditionOutput as output from UNet.

* make style
Co-authored-by: default avatarMishig Davaadorj <dmishig@gmail.com>
Co-authored-by: default avatarMishig Davaadorj <mishig.davaadorj@coloradocollege.edu>
Co-authored-by: default avatarSuraj Patil <surajp815@gmail.com>
Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      d8b0e4f4
    • Kashif Rasul's avatar
      Karras VE, DDIM and DDPM flax schedulers (#508) · b34be039
      Kashif Rasul authored 
      * beta never changes removed from state

* fix typos in docs

* removed unused var

* initial ddim flax scheduler

* import

* added dummy objects

* fix style

* fix typo

* docs

* fix typo in comment

* set return type

* added flax ddom

* fix style

* remake

* pass PRNG key as argument and split before use

* fix doc string

* use config

* added flax Karras VE scheduler

* make style

* fix dummy

* fix ndarray type annotation

* replace returns a new state

* added lms_discrete scheduler

* use self.config

* add_noise needs state

* use config

* use config

* docstring

* added flax score sde ve

* fix imports

* fix typos
      b34be039
  31. 14 Sep, 2022 1 commit
  33. 13 Sep, 2022 2 commits
  35. 08 Sep, 2022 4 commits
  37. 07 Sep, 2022 1 commit
  39. 05 Sep, 2022 1 commit
  41. 01 Sep, 2022 1 commit
  43. 30 Aug, 2022 1 commit