1. 05 Jul, 2023 1 commit
    • Pedro Cuenca's avatar
      Add `timestep_spacing` and `steps_offset` to schedulers (#3947) · 07c9a08e
      Pedro Cuenca authored
      
      
      * Add timestep_spacing to DDPM, LMSDiscrete, PNDM.
      
      * Remove spurious line.
      
      * More easy schedulers.
      
      * Add `linspace` to DDIM
      
      * Noise sigma for `trailing`.
      
      * Add timestep_spacing to DEISMultistepScheduler.
      
      Not sure the range is the way it was intended.
      
      * Fix: remove line used to debug.
      
      * Support timestep_spacing in DPMSolverMultistep, DPMSolverSDE, UniPC
      
      * Fix: convert to numpy.
      
      * Use sched. defaults when instantiating from_config
      
      For params not present in the original configuration.
      
      This makes it possible to switch pipeline schedulers even if they use
      different timestep_spacing (or any other param).
      
      * Apply suggestions from code review
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * Missing args in DPMSolverMultistep
      
      * Test: default args not in config
      
      * Style
      
      * Fix scheduler name in test
      
      * Remove duplicated entries
      
      * Add test for solver_type
      
      This test currently fails in main. When switching from DEIS to UniPC,
      solver_type is "logrho" (the default value from DEIS), which gets
      translated to "bh1" by UniPC. This is different to the default value for
      UniPC: "bh2". This is where the translation happens: https://github.com/huggingface/diffusers/blob/36d22d0709dc19776e3016fb3392d0f5578b0ab2/src/diffusers/schedulers/scheduling_unipc_multistep.py#L171
      
      
      
      * UniPC: use same default for solver_type
      
      Fixes a bug when switching from UniPC from another scheduler (i.e.,
      DEIS) that uses a different solver type. The solver is now the same as
      if we had instantiated the scheduler directly.
      
      * do not save use default values
      
      * fix more
      
      * fix all
      
      * fix schedulers
      
      * fix more
      
      * finish for real
      
      * finish for real
      
      * flaky tests
      
      * Update tests/pipelines/stable_diffusion/test_stable_diffusion_pix2pix_zero.py
      
      * Default steps_offset to 0.
      
      * Add missing docstrings
      
      * Apply suggestions from code review
      
      ---------
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      07c9a08e
  2. 03 Jul, 2023 1 commit
    • Patrick von Platen's avatar
      Correct controlnet out of list error (#3928) · 2e8668f0
      Patrick von Platen authored
      * Correct controlnet out of list error
      
      * Apply suggestions from code review
      
      * correct tests
      
      * correct tests
      
      * fix
      
      * test all
      
      * Apply suggestions from code review
      
      * test all
      
      * test all
      
      * Apply suggestions from code review
      
      * Apply suggestions from code review
      
      * fix more tests
      
      * Fix more
      
      * Apply suggestions from code review
      
      * finish
      
      * Apply suggestions from code review
      
      * Update src/diffusers/schedulers/scheduling_k_dpm_2_ancestral_discrete.py
      
      * finish
      2e8668f0
  3. 28 Jun, 2023 1 commit
  4. 20 Jun, 2023 1 commit
  5. 07 Jun, 2023 1 commit
  6. 22 May, 2023 2 commits
  7. 16 May, 2023 1 commit
  8. 15 May, 2023 1 commit
  9. 12 May, 2023 1 commit
  10. 06 May, 2023 1 commit
  11. 05 May, 2023 2 commits
  12. 03 May, 2023 1 commit
  13. 27 Apr, 2023 1 commit
    • Nipun Jindal's avatar
      [2064]: Add stochastic sampler (sample_dpmpp_sde) (#3020) · fd512d74
      Nipun Jindal authored
      
      
      * [2064]: Add stochastic sampler
      
      * [2064]: Add stochastic sampler
      
      * [2064]: Add stochastic sampler
      
      * [2064]: Add stochastic sampler
      
      * [2064]: Add stochastic sampler
      
      * [2064]: Add stochastic sampler
      
      * [2064]: Add stochastic sampler
      
      * Review comments
      
      * [Review comment]: Add is_torchsde_available()
      
      * [Review comment]: Test and docs
      
      * [Review comment]
      
      * [Review comment]
      
      * [Review comment]
      
      * [Review comment]
      
      * [Review comment]
      
      ---------
      Co-authored-by: default avatarnjindal <njindal@adobe.com>
      fd512d74
  14. 21 Apr, 2023 1 commit
  15. 17 Apr, 2023 1 commit
  16. 14 Apr, 2023 1 commit
    • Will Berman's avatar
      ddpm custom timesteps (#3007) · b811964a
      Will Berman authored
      add custom timesteps test
      
      add custom timesteps descending order check
      
      docs
      
      timesteps -> custom_timesteps
      
      can only pass one of num_inference_steps and timesteps
      b811964a
  17. 12 Apr, 2023 1 commit
  18. 11 Apr, 2023 1 commit
    • 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
  19. 10 Apr, 2023 7 commits
  20. 06 Apr, 2023 2 commits
  21. 14 Mar, 2023 1 commit
    • clarencechen's avatar
      Add support for different model prediction types in DDIMInverseScheduler (#2619) · ee71d9d0
      clarencechen authored
      
      
      * Add support for different model prediction types in DDIMInverseScheduler
      Resolve alpha_prod_t_prev index issue for final step of inversion
      
      * Fix old bug introduced when prediction type is "sample"
      
      * Add support for sample clipping for numerical stability and deprecate old kwarg
      
      * Detach sample, alphas, betas
      
      Derive predicted noise from model output before dist. regularization
      
      Style cleanup
      
      * Log loss for debugging
      
      * Revert "Log loss for debugging"
      
      This reverts commit 76ea9c856f99f4c8eca45a0b1801593bb982584b.
      
      * Add comments
      
      * Add inversion equivalence test
      
      * Add expected data for Pix2PixZero pipeline tests with SD 2
      
      * Update tests/pipelines/stable_diffusion/test_stable_diffusion_pix2pix_zero.py
      
      * Remove cruft and add more explanatory comments
      
      ---------
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      ee71d9d0
  22. 10 Mar, 2023 1 commit
  23. 09 Mar, 2023 2 commits
  24. 07 Mar, 2023 1 commit
  25. 01 Mar, 2023 1 commit
  26. 17 Feb, 2023 2 commits
  27. 16 Feb, 2023 3 commits