1. 19 May, 2025 1 commit
  2. 10 Jan, 2025 1 commit
  3. 07 Jan, 2025 2 commits
  4. 10 May, 2024 1 commit
    • Mark Van Aken's avatar
      #7535 Update FloatTensor type hints to Tensor (#7883) · be4afa0b
      Mark Van Aken authored
      * 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
      be4afa0b
  5. 19 Apr, 2024 1 commit
  6. 28 Feb, 2024 1 commit
  7. 08 Feb, 2024 1 commit
  8. 20 Nov, 2023 1 commit
  9. 02 Oct, 2023 1 commit
  10. 28 Jul, 2023 1 commit
  11. 11 Apr, 2023 3 commits
    • Patrick von Platen's avatar
      make style · 091a0582
      Patrick von Platen authored
      091a0582
    • J N Hearns's avatar
      Fix imports for composable_stable_diffusion pipeline (#3002) · 881a6b58
      J N Hearns authored
      * Update composable_stable_diffusion.py
      
      Fix imports
      
      * Formatting
      
      * Formatting
      
      * Formatting
      881a6b58
    • Patrick von Platen's avatar
      Fix config prints and save, load of pipelines (#2849) · 8b451eb6
      Patrick von Platen authored
      * [Config] Fix config prints and save, load
      
      * Only use potential nn.Modules for dtype and device
      
      * Correct vae image processor
      
      * make sure in_channels is not accessed directly
      
      * make sure in channels is only accessed via config
      
      * Make sure schedulers only access config attributes
      
      * Make sure to access config in SAG
      
      * Fix vae processor and make style
      
      * add tests
      
      * uP
      
      * make style
      
      * Fix more naming issues
      
      * Final fix with vae config
      
      * change more
      8b451eb6
  12. 23 Mar, 2023 1 commit
  13. 01 Mar, 2023 1 commit
  14. 14 Feb, 2023 1 commit
  15. 07 Feb, 2023 1 commit
  16. 06 Feb, 2023 1 commit
  17. 30 Dec, 2022 1 commit
  18. 19 Dec, 2022 1 commit
    • Nan Liu's avatar
      update composable diffusion for an updated diffuser library (#1697) · 6f150263
      Nan Liu authored
      * update composable diffusion for an updated diffuser library
      
      * fix style/quality for code
      
      * Revert "fix style/quality for code"
      
      This reverts commit 71f23497639fe69de00d93cf91edc31b08dcd7a4.
      
      * update style
      
      * reduce memory usage by computing score sequentially
      6f150263
  19. 07 Nov, 2022 1 commit
  20. 26 Oct, 2022 1 commit
  21. 25 Oct, 2022 1 commit
  22. 24 Oct, 2022 1 commit
  23. 13 Oct, 2022 3 commits
  24. 11 Oct, 2022 2 commits
  25. 06 Oct, 2022 1 commit
    • Suraj Patil's avatar
      allow multiple generations per prompt (#741) · c119dc4c
      Suraj Patil authored
      * compute text embeds per prompt
      
      * don't repeat uncond prompts
      
      * repeat separatly
      
      * update image2image
      
      * fix repeat uncond embeds
      
      * adapt inpaint pipeline
      
      * ifx uncond tokens in img2img
      
      * add tests and fix ucond embeds in im2img and inpaint pipe
      c119dc4c
  26. 05 Oct, 2022 3 commits
  27. 04 Oct, 2022 1 commit
  28. 03 Oct, 2022 2 commits
  29. 02 Oct, 2022 1 commit
  30. 30 Sep, 2022 1 commit
    • Nouamane Tazi's avatar
      Optimize Stable Diffusion (#371) · 9ebaea54
      Nouamane Tazi authored
      * initial commit
      
      * make UNet stream capturable
      
      * try to fix noise_pred value
      
      * remove cuda graph and keep NB
      
      * non blocking unet with PNDMScheduler
      
      * make timesteps np arrays for pndm scheduler
      because lists don't get formatted to tensors in `self.set_format`
      
      * make max async in pndm
      
      * use channel last format in unet
      
      * avoid moving timesteps device in each unet call
      
      * avoid memcpy op in `get_timestep_embedding`
      
      * add `channels_last` kwarg to `DiffusionPipeline.from_pretrained`
      
      * update TODO
      
      * replace `channels_last` kwarg with `memory_format` for more generality
      
      * revert the channels_last changes to leave it for another PR
      
      * remove non_blocking when moving input ids to device
      
      * remove blocking from all .to() operations at beginning of pipeline
      
      * fix merging
      
      * fix merging
      
      * model can run in other precisions without autocast
      
      * attn refactoring
      
      * Revert "attn refactoring"
      
      This reverts commit 0c70c0e189cd2c4d8768274c9fcf5b940ee310fb.
      
      * remove restriction to run conv_norm in fp32
      
      * use `baddbmm` instead of `matmul`for better in attention for better perf
      
      * removing all reshapes to test perf
      
      * Revert "removing all reshapes to test perf"
      
      This reverts commit 006ccb8a8c6bc7eb7e512392e692a29d9b1553cd.
      
      * add shapes comments
      
      * hardcore whats needed for jitting
      
      * Revert "hardcore whats needed for jitting"
      
      This reverts commit 2fa9c698eae2890ac5f8e367ca80532ecf94df9a.
      
      * Revert "remove restriction to run conv_norm in fp32"
      
      This reverts commit cec592890c32da3d1b78d38b49e4307aedf459b9.
      
      * revert using baddmm in attention's forward
      
      * cleanup comment
      
      * remove restriction to run conv_norm in fp32. no quality loss was noticed
      
      This reverts commit cc9bc1339c998ebe9e7d733f910c6d72d9792213.
      
      * add more optimizations techniques to docs
      
      * Revert "add shapes comments"
      
      This reverts commit 31c58eadb8892f95478cdf05229adf678678c5f4.
      
      * apply suggestions
      
      * make quality
      
      * apply suggestions
      
      * styling
      
      * `scheduler.timesteps` are now arrays so we dont need .to()
      
      * remove useless .type()
      
      * use mean instead of max in `test_stable_diffusion_inpaint_pipeline_k_lms`
      
      * move scheduler timestamps to correct device if tensors
      
      * add device to `set_timesteps` in LMSD scheduler
      
      * `self.scheduler.set_timesteps` now uses device arg for schedulers that accept it
      
      * quick fix
      
      * styling
      
      * remove kwargs from schedulers `set_timesteps`
      
      * revert to using max in K-LMS inpaint pipeline test
      
      * Revert "`self.scheduler.set_timesteps` now uses device arg for schedulers that accept it"
      
      This reverts commit 00d5a51e5c20d8d445c8664407ef29608106d899.
      
      * move timesteps to correct device before loop in SD pipeline
      
      * apply previous fix to other SD pipelines
      
      * UNet now accepts tensor timesteps even on wrong device, to avoid errors
      - it shouldnt affect performance if timesteps are alrdy on correct device
      - it does slow down performance if they're on the wrong device
      
      * fix pipeline when timesteps are arrays with strides
      9ebaea54
  31. 27 Sep, 2022 1 commit
    • Kashif Rasul's avatar
      [Pytorch] Pytorch only schedulers (#534) · bd8df2da
      Kashif Rasul authored
      
      
      * pytorch only schedulers
      
      * fix style
      
      * remove match_shape
      
      * pytorch only ddpm
      
      * remove SchedulerMixin
      
      * remove numpy from karras_ve
      
      * fix types
      
      * remove numpy from lms_discrete
      
      * remove numpy from pndm
      
      * fix typo
      
      * remove mixin and numpy from sde_vp and ve
      
      * remove remaining tensor_format
      
      * fix style
      
      * sigmas has to be torch tensor
      
      * removed set_format in readme
      
      * remove set format from docs
      
      * remove set_format from pipelines
      
      * update tests
      
      * fix typo
      
      * continue to use mixin
      
      * fix imports
      
      * removed unsed imports
      
      * match shape instead of assuming image shapes
      
      * remove import typo
      
      * update call to add_noise
      
      * use math instead of numpy
      
      * fix t_index
      
      * removed commented out numpy tests
      
      * timesteps needs to be discrete
      
      * cast timesteps to int in flax scheduler too
      
      * fix device mismatch issue
      
      * small fix
      
      * Update src/diffusers/schedulers/scheduling_pndm.py
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      bd8df2da