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Merge pull request #3061 from leppie/sde-noise-sampler-seeds 

SDE noise sampler seeds
pull/3063/head
Vladimir Mandic 2024-04-17 08:02:22 -04:00 committed by GitHub
parent 2ad029834d 9d2d3b6d6e
commit 6f61bcf6e7
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GPG Key ID: B5690EEEBB952194
1 changed files with 3 additions and 3 deletions
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modules/processing_diffusers.py
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@ -225,9 +225,9 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
args['negative_prompt'] = negative_prompts args['negative_prompt'] = negative_prompts
if hasattr(model, 'scheduler') and hasattr(model.scheduler, 'noise_sampler_seed') and hasattr(model.scheduler, 'noise_sampler'): if hasattr(model, 'scheduler') and hasattr(model.scheduler, 'noise_sampler_seed') and hasattr(model.scheduler, 'noise_sampler'):
model.scheduler.noise_sampler = None # noise needs to be reset instead of using cached values model.scheduler.noise_sampler = None # noise needs to be reset instead of using cached values
model.scheduler.noise_sampler_seed = p.seeds[0] # some schedulers have internal noise generator and do not use pipeline generator model.scheduler.noise_sampler_seed = p.seeds # some schedulers have internal noise generator and do not use pipeline generator
if 'noise_sampler_seed' in possible: if 'noise_sampler_seed' in possible:
args['noise_sampler_seed'] = p.seeds[0] args['noise_sampler_seed'] = p.seeds
if 'guidance_scale' in possible: if 'guidance_scale' in possible:
args['guidance_scale'] = p.cfg_scale args['guidance_scale'] = p.cfg_scale
if 'generator' in possible and generator is not None: if 'generator' in possible and generator is not None:
@ -399,6 +399,7 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
shared.sd_model = update_pipeline(shared.sd_model, p) shared.sd_model = update_pipeline(shared.sd_model, p)
shared.log.info(f'Base: class={shared.sd_model.__class__.__name__}') shared.log.info(f'Base: class={shared.sd_model.__class__.__name__}')
update_sampler(shared.sd_model)
base_args = set_pipeline_args( base_args = set_pipeline_args(
model=shared.sd_model, model=shared.sd_model,
prompts=p.prompts, prompts=p.prompts,
@ -415,7 +416,6 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
clip_skip=p.clip_skip, clip_skip=p.clip_skip,
desc='Base', desc='Base',
) )
update_sampler(shared.sd_model)
shared.state.sampling_steps = base_args.get('num_inference_steps', p.steps) shared.state.sampling_steps = base_args.get('num_inference_steps', p.steps)
p.extra_generation_params['Pipeline'] = shared.sd_model.__class__.__name__ p.extra_generation_params['Pipeline'] = shared.sd_model.__class__.__name__
if shared.opts.scheduler_eta is not None and shared.opts.scheduler_eta > 0 and shared.opts.scheduler_eta < 1: if shared.opts.scheduler_eta is not None and shared.opts.scheduler_eta > 0 and shared.opts.scheduler_eta < 1: