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refactor schedulers first part

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Vladimir Mandic
2023-09-21 13:19:55 -04:00
parent 36324361bd
commit 4518cfb3b1
12 changed files with 50 additions and 53 deletions
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modules/processing_diffusers.py
+4 -4
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@@ -343,7 +343,7 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
prompts_2=[p.refiner_prompt] if len(p.refiner_prompt) > 0 else prompts,
negative_prompts_2=[p.refiner_negative] if len(p.refiner_negative) > 0 else negative_prompts,
num_inference_steps=calculate_base_steps(),
eta=shared.opts.eta_ddim,
eta=shared.opts.scheduler_eta,
guidance_rescale=p.diffusers_guidance_rescale,
denoising_start=0 if use_refiner_start else p.refiner_start if use_denoise_start else None,
denoising_end=p.refiner_start if use_refiner_start else 1 if use_denoise_start else None,
@@ -353,7 +353,7 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
**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
p.extra_generation_params["Eta"] = shared.opts.scheduler_eta if shared.opts.scheduler_eta is not None and shared.opts.scheduler_eta > 0 else None
try:
output = shared.sd_model(**base_args) # pylint: disable=not-callable
except AssertionError as e:
@@ -395,7 +395,7 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
prompts_2=[p.refiner_prompt] if len(p.refiner_prompt) > 0 else prompts,
negative_prompts_2=[p.refiner_negative] if len(p.refiner_negative) > 0 else negative_prompts,
num_inference_steps=int(p.hr_second_pass_steps // p.denoising_strength + 1),
eta=shared.opts.eta_ddim,
eta=shared.opts.scheduler_eta,
guidance_scale=p.image_cfg_scale if p.image_cfg_scale is not None else p.cfg_scale,
guidance_rescale=p.diffusers_guidance_rescale,
output_type='latent' if hasattr(shared.sd_model, 'vae') else 'np',
@@ -448,7 +448,7 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
prompts=[p.refiner_prompt] if len(p.refiner_prompt) > 0 else prompts[i],
negative_prompts=[p.refiner_negative] if len(p.refiner_negative) > 0 else negative_prompts[i],
num_inference_steps=int(p.refiner_steps // (1 - p.refiner_start)) if p.refiner_start > 0 and p.refiner_start < 1 and refiner_is_sdxl else int(p.refiner_steps // p.denoising_strength + 1) if refiner_is_sdxl else p.refiner_steps,
eta=shared.opts.eta_ddim,
eta=shared.opts.scheduler_eta,
strength=p.denoising_strength,
guidance_scale=p.image_cfg_scale if p.image_cfg_scale is not None else p.cfg_scale,
guidance_rescale=p.diffusers_guidance_rescale,