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fix diffusers samplers

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Vladimir Mandic
2023-07-15 22:40:00 -04:00
parent f773c782fa
commit e2b33b81d3
7 changed files with 43 additions and 37 deletions
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modules/processing.py
+12 -13
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@@ -278,7 +278,7 @@ class Processed:
self.sd_model_hash = shared.sd_model.sd_model_hash
self.seed_resize_from_w = p.seed_resize_from_w
self.seed_resize_from_h = p.seed_resize_from_h
self.denoising_strength = getattr(p, 'denoising_strength', None)
self.denoising_strength = p.denoising_strength
self.extra_generation_params = p.extra_generation_params
self.index_of_first_image = index_of_first_image
self.styles = p.styles
@@ -466,7 +466,7 @@ def create_infotext(p: StableDiffusionProcessing, all_prompts, all_seeds, all_su
"Variation seed": None if p.subseed_strength == 0 else all_subseeds[index],
"Variation seed strength": None if p.subseed_strength == 0 else p.subseed_strength,
"Seed resize from": None if p.seed_resize_from_w == 0 or p.seed_resize_from_h == 0 else f"{p.seed_resize_from_w}x{p.seed_resize_from_h}",
"Denoising strength": getattr(p, 'denoising_strength', None),
"Denoising strength": p.denoising_strength,
"Conditional mask weight": getattr(p, "inpainting_mask_weight", shared.opts.inpainting_mask_weight) if p.is_using_inpainting_conditioning else None,
"Clip skip": p.clip_skip if p.clip_skip > 1 else None,
"ENSD": opts.eta_noise_seed_delta if uses_ensd else None,
@@ -728,11 +728,11 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
del samples_ddim
elif shared.backend == Backend.DIFFUSERS:
if (not hasattr(shared.sd_model.scheduler, 'name')) or (shared.sd_model.scheduler.name != p.sampler_name):
sampler = sd_samplers.all_samplers_map.get(p.sampler_name, None)
if sampler is None:
sampler = sd_samplers.all_samplers_map.get("UniPC")
shared.sd_model.scheduler = sd_samplers.create_sampler(sampler.name, shared.sd_model) # TODO(Patrick): For wrapped pipelines this is currently a no-op
# if (not hasattr(shared.sd_model.scheduler, 'name')) or (shared.sd_model.scheduler.name != p.sampler_name):
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
cross_attention_kwargs={}
if lora_state['active']:
@@ -746,7 +746,6 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
# TODO(PVP): change out to latents once possible with `diffusers`
task_specific_kwargs = {"image": p.init_images[0], "mask_image": p.image_mask, "strength": p.denoising_strength}
shared.sd_model.to(devices.device)
pipe_args = set_pipeline_args(
model=shared.sd_model,
@@ -766,11 +765,11 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
shared.log.debug('Moving base model to CPU')
shared.sd_model.to('cpu')
if (not hasattr(shared.sd_refiner.scheduler, 'name')) or (shared.sd_refiner.scheduler.name != p.latent_sampler):
sampler = sd_samplers.all_samplers_map.get(p.latent_sampler, None)
if sampler is None:
sampler = sd_samplers.all_samplers_map.get("UniPC")
shared.sd_refiner.scheduler = sd_samplers.create_sampler(sampler.name, shared.sd_refiner) # TODO(Patrick): For wrapped pipelines this is currently a no-op
# if (not hasattr(shared.sd_refiner.scheduler, 'name')) or (shared.sd_refiner.scheduler.name != p.latent_sampler):
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_refiner) # TODO(Patrick): For wrapped pipelines this is currently a no-op
shared.sd_refiner.to(devices.device)
devices.torch_gc()