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Code Activity

[Schedulers] Fix 2nd order other than heun (#5526)

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* [Schedulers] Fix 2nd order other than heun

* Apply suggestions from code review
This commit is contained in:
Patrick von Platen
2023-10-25 14:39:56 +02:00
committed by GitHub
parent 0fc25715a1
commit dc943eb99d
3 changed files with 9 additions and 9 deletions
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6
src/diffusers/pipelines/controlnet/pipeline_controlnet_inpaint_sd_xl.py
View File

@@ -898,9 +898,9 @@ class StableDiffusionXLControlNetInpaintPipeline(
)
num_inference_steps = (timesteps < discrete_timestep_cutoff).sum().item()
if self.scheduler.order == 2:
# if the scheduler is a 2nd order scheduler we ALWAYS have to do +1
# because `num_inference_steps` will always be even given that every timestep
if self.scheduler.order == 2 and num_inference_steps % 2 == 0:
# if the scheduler is a 2nd order scheduler we might have to do +1
# because `num_inference_steps` might be even given that every timestep
# (except the highest one) is duplicated. If `num_inference_steps` is even it would
# mean that we cut the timesteps in the middle of the denoising step
# (between 1st and 2nd devirative) which leads to incorrect results. By adding 1

6
src/diffusers/pipelines/stable_diffusion_xl/pipeline_stable_diffusion_xl_img2img.py
View File

@@ -555,9 +555,9 @@ class StableDiffusionXLImg2ImgPipeline(
)
num_inference_steps = (timesteps < discrete_timestep_cutoff).sum().item()
if self.scheduler.order == 2:
# if the scheduler is a 2nd order scheduler we ALWAYS have to do +1
# because `num_inference_steps` will always be even given that every timestep
if self.scheduler.order == 2 and num_inference_steps % 2 == 0:
# if the scheduler is a 2nd order scheduler we might have to do +1
# because `num_inference_steps` might be even given that every timestep
# (except the highest one) is duplicated. If `num_inference_steps` is even it would
# mean that we cut the timesteps in the middle of the denoising step
# (between 1st and 2nd devirative) which leads to incorrect results. By adding 1

6
src/diffusers/pipelines/stable_diffusion_xl/pipeline_stable_diffusion_xl_inpaint.py
View File

@@ -840,9 +840,9 @@ class StableDiffusionXLInpaintPipeline(
)
num_inference_steps = (timesteps < discrete_timestep_cutoff).sum().item()
if self.scheduler.order == 2:
# if the scheduler is a 2nd order scheduler we ALWAYS have to do +1
# because `num_inference_steps` will always be even given that every timestep
if self.scheduler.order == 2 and num_inference_steps % 2 == 0:
# if the scheduler is a 2nd order scheduler we might have to do +1
# because `num_inference_steps` might be even given that every timestep
# (except the highest one) is duplicated. If `num_inference_steps` is even it would
# mean that we cut the timesteps in the middle of the denoising step
# (between 1st and 2nd devirative) which leads to incorrect results. By adding 1