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Diffusers fix hires sampler

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Disty0
2023-09-16 14:38:55 +03:00
parent 71631b7a36
commit b13494a142
1 changed files with 8 additions and 4 deletions
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modules/processing_diffusers.py
+8 -4
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@@ -281,9 +281,8 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
pass #Do nothing if compile is disabled
is_karras_compatible = shared.sd_model.__class__.__init__.__annotations__.get("scheduler", None) == diffusers.schedulers.scheduling_utils.KarrasDiffusionSchedulers
use_sampler = p.sampler_name if not p.is_hr_pass else p.latent_sampler
if (not hasattr(shared.sd_model.scheduler, 'name')) or (shared.sd_model.scheduler.name != use_sampler) and (use_sampler != 'Default') and is_karras_compatible:
sampler = sd_samplers.all_samplers_map.get(use_sampler, None)
if (not hasattr(shared.sd_model.scheduler, 'name')) or (shared.sd_model.scheduler.name != p.sampler_name) and (p.sampler_name != 'Default') and is_karras_compatible:
sampler = sd_samplers.all_samplers_map.get(p.sampler_name, None)
if sampler is None:
sampler = sd_samplers.all_samplers_map.get("UniPC")
sd_samplers.create_sampler(sampler.name, shared.sd_model) # TODO(Patrick): For wrapped pipelines this is currently a no-op
@@ -380,6 +379,11 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
output.images = hires_resize(latents=output.images)
if latent_scale_mode is not None or p.hr_force:
p.ops.append('hires')
if (not hasattr(shared.sd_model.scheduler, 'name')) or (shared.sd_model.scheduler.name != p.latent_sampler) and (p.latent_sampler != 'Default') and is_karras_compatible:
sampler = sd_samplers.all_samplers_map.get(p.latent_sampler, None)
if sampler is None:
sampler = sd_samplers.all_samplers_map.get("UniPC")
sd_samplers.create_sampler(sampler.name, shared.sd_model) # TODO(Patrick): For wrapped pipelines this is currently a no-op
recompile_model(hires=True)
sd_models.set_diffuser_pipe(shared.sd_model, sd_models.DiffusersTaskType.IMAGE_2_IMAGE)
hires_args = set_pipeline_args(
@@ -412,7 +416,7 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
shared.sd_model.to(devices.cpu)
devices.torch_gc()
if (not hasattr(shared.sd_refiner.scheduler, 'name')) or (shared.sd_refiner.scheduler.name != p.latent_sampler) and (p.sampler_name != 'Default'):
if (not hasattr(shared.sd_refiner.scheduler, 'name')) or (shared.sd_refiner.scheduler.name != p.latent_sampler) and (p.latent_sampler != 'Default'):
sampler = sd_samplers.all_samplers_map.get(p.latent_sampler, None)
if sampler is None:
sampler = sd_samplers.all_samplers_map.get("UniPC")