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Vladimir Mandic
2023-08-14 07:50:12 +00:00
parent 88fff06c9e
commit eeca263bd2
5 changed files with 36 additions and 21 deletions
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modules/processing_diffusers.py
+15
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@@ -160,6 +160,14 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
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
sampler_options = f'type:{shared.opts.schedulers_prediction_type} ' if shared.opts.schedulers_prediction_type != 'default' else ''
sampler_options += 'no_karras ' if not shared.opts.schedulers_use_karras else ''
sampler_options += 'no_low_order' if not shared.opts.schedulers_use_loworder else ''
sampler_options += 'dynamic_thresholding' if shared.opts.schedulers_use_thresholding else ''
sampler_options += f'solver:{shared.opts.schedulers_dpm_solver}' if shared.opts.schedulers_dpm_solver != 'sde-dpmsolver++' else ''
sampler_options += f'beta:{shared.opts.schedulers_beta_schedule}:{shared.opts.schedulers_beta_start}:{shared.opts.schedulers_beta_end}' if shared.opts.schedulers_beta_schedule != 'default' else ''
p.extra_generation_params['Sampler options'] = sampler_options if len(sampler_options) > 0 else None
p.extra_generation_params['Pipeline'] = shared.sd_model.__class__.__name__
cross_attention_kwargs={}
if len(getattr(p, 'init_images', [])) > 0:
@@ -201,6 +209,8 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
clip_skip=p.clip_skip,
**task_specific_kwargs
)
p.extra_generation_params['CFG rescale'] = p.diffusers_guidance_rescale
p.extra_generation_params["Eta DDIM"] = shared.opts.eta_ddim if shared.opts.eta_ddim is not None and shared.opts.eta_ddim > 0 else None
output = shared.sd_model(**pipe_args) # pylint: disable=not-callable
if shared.state.interrupted or shared.state.skipped:
unload_diffusers_lora()
@@ -210,6 +220,7 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
output.images = vae_decode(output.images, shared.sd_model) if p.full_quality else taesd_vae_decode(output.images, shared.sd_model)
if lora_state['active']:
p.extra_generation_params['Lora method'] = shared.opts.diffusers_lora_loader
unload_diffusers_lora()
if refiner_enabled:
@@ -256,6 +267,10 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
clip_skip=p.clip_skip,
)
refiner_output = shared.sd_refiner(**pipe_args) # pylint: disable=not-callable
p.extra_generation_params['Refiner CFG scale'] = p.image_cfg_scale if p.image_cfg_scale is not None else None
p.extra_generation_params['Refiner start'] = p.refiner_start
p.extra_generation_params["Hires steps"] = p.hr_second_pass_steps
if not shared.state.interrupted and not shared.state.skipped:
refiner_images = vae_decode(refiner_output.images, shared.sd_refiner)
results.append(refiner_images[0])