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  1. 16 Nov, 2022 1 commit
  3. 15 Nov, 2022 2 commits
  5. 09 Nov, 2022 1 commit
  7. 08 Nov, 2022 1 commit
  9. 06 Nov, 2022 1 commit
    • Cheng Lu's avatar
      Add multistep DPM-Solver discrete scheduler (#1132) · b4a1ed85
      Cheng Lu authored 
      

* add dpmsolver discrete pytorch scheduler

* fix some typos in dpm-solver pytorch

* add dpm-solver pytorch in stable-diffusion pipeline

* add jax/flax version dpm-solver

* change code style

* change code style

* add docs

* add `add_noise` method for dpmsolver

* add pytorch unit test for dpmsolver

* add dummy object for pytorch dpmsolver

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

* Update tests/test_config.py
Co-authored-by: default avatarSuraj Patil <surajp815@gmail.com>

* Update tests/test_config.py
Co-authored-by: default avatarSuraj Patil <surajp815@gmail.com>

* resolve the code comments

* rename the file

* change class name

* fix code style

* add auto docs for dpmsolver multistep

* add more explanations for the stabilizing trick (for steps < 15)

* delete the dummy file

* change the API name of predict_epsilon, algorithm_type and solver_type

* add compatible lists
Co-authored-by: default avatarSuraj Patil <surajp815@gmail.com>
      b4a1ed85
  11. 04 Nov, 2022 2 commits
  13. 03 Nov, 2022 6 commits
    • Patrick von Platen's avatar
      make style · bde4880c
      Patrick von Platen authored
      bde4880c
    • Patrick von Platen's avatar
      Correct VQDiffusion Pipeline import · 33108bfa
      Patrick von Platen authored
      33108bfa
    • Patrick von Platen's avatar
      fix copies · 988c8222
      Patrick von Platen authored
      988c8222
    • 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
  15. 02 Nov, 2022 2 commits
    • Lewington-pitsos's avatar
      Integration tests precision improvement for inpainting (#1052) · 8ee21915
      Lewington-pitsos authored 
      

* improve test precision

get tests passing with greater precision using lewington images

* make old numpy load function a wrapper around a more flexible numpy loading function

* adhere to black formatting

* add more black formatting

* adhere to isort

* loosen precision and replace path
Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      8ee21915
    • MatthieuTPHR's avatar
      Up to 2x speedup on GPUs using memory efficient attention (#532) · 98c42134
      MatthieuTPHR authored 
      

* 2x speedup using memory efficient attention

* remove einops dependency

* Swap K, M in op instantiation

* Simplify code, remove unnecessary maybe_init call and function, remove unused self.scale parameter

* make xformers a soft dependency

* remove one-liner functions

* change one letter variable to appropriate names

* Remove Env variable dependency, remove MemoryEfficientCrossAttention class and use enable_xformers_memory_efficient_attention method

* Add memory efficient attention toggle to img2img and inpaint pipelines

* Clearer management of xformers' availability

* update optimizations markdown to add info about memory efficient attention

* add benchmarks for TITAN RTX

* More detailed explanation of how the mem eff benchmark were ran

* Removing autocast from optimization markdown

* import_utils: import torch only if is available
Co-authored-by: default avatarNouamane Tazi <nouamane98@gmail.com>
      98c42134
  17. 31 Oct, 2022 2 commits
  19. 28 Oct, 2022 3 commits
  21. 25 Oct, 2022 1 commit
  23. 24 Oct, 2022 1 commit
  25. 20 Oct, 2022 2 commits
  27. 19 Oct, 2022 2 commits
  29. 18 Oct, 2022 1 commit
  31. 14 Oct, 2022 1 commit
  33. 13 Oct, 2022 1 commit
  35. 12 Oct, 2022 1 commit
  37. 11 Oct, 2022 1 commit
    • Akash Pannu's avatar
      Flax: Trickle down `norm_num_groups` (#789) · a1242044
      Akash Pannu authored 
      * pass norm_num_groups param and add tests

* set resnet_groups for FlaxUNetMidBlock2D

* fixed docstrings

* fixed typo

* using is_flax_available util and created require_flax decorator
      a1242044
  39. 06 Oct, 2022 1 commit
  41. 05 Oct, 2022 1 commit
  43. 04 Oct, 2022 2 commits
    • Pedro Cuenca's avatar
      Fix import if PyTorch is not installed (#715) · 215bb408
      Pedro Cuenca authored 
      * Fix import if PyTorch is not installed.

* Style (blank line)
      215bb408
    • Pi Esposito's avatar
      add accelerate to load models with smaller memory footprint (#361) · 4d1cce2f
      Pi Esposito authored 
      

* add accelerate to load models with smaller memory footprint

* remove low_cpu_mem_usage as it is reduntant

* move accelerate init weights context to modelling utils

* add test to ensure results are the same when loading with accelerate

* add tests to ensure ram usage gets lower when using accelerate

* move accelerate logic to single snippet under modelling utils and remove it from configuration utils

* format code using to pass quality check

* fix imports with isor

* add accelerate to test extra deps

* only import accelerate if device_map is set to auto

* move accelerate availability check to diffusers import utils

* format code
Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      4d1cce2f
  45. 03 Oct, 2022 1 commit
  47. 24 Sep, 2022 1 commit
  49. 21 Sep, 2022 1 commit
  51. 20 Sep, 2022 1 commit