Use better way to impl
This commit is contained in:
Kohaku-Blueleaf
parent
1846ad36a3
commit
70650f87a4
@ -106,7 +106,7 @@ class StableDiffusionProcessing:
|
||||
"""
|
||||
The first set of paramaters: sd_models -> do_not_reload_embeddings represent the minimum required to create a StableDiffusionProcessing
|
||||
"""
|
||||
def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt: str = "", styles: List[str] = None, seed: int = -1, subseed: int = -1, subseed_strength: float = 0, seed_resize_from_h: int = -1, seed_resize_from_w: int = -1, seed_enable_extras: bool = True, sampler_name: str = None, batch_size: int = 1, n_iter: int = 1, steps: int = 50, cfg_scale: float = 7.0, width: int = 512, height: int = 512, restore_faces: bool = False, tiling: bool = False, do_not_save_samples: bool = False, do_not_save_grid: bool = False, extra_generation_params: Dict[Any, Any] = None, overlay_images: Any = None, negative_prompt: str = None, eta: float = None, do_not_reload_embeddings: bool = False, denoising_strength: float = 0, ddim_discretize: str = None, s_min_uncond: float = 0.0, s_churn: float = 0.0, s_tmax: float = None, s_tmin: float = 0.0, s_noise: float = 1.0, override_settings: Dict[str, Any] = None, override_settings_restore_afterwards: bool = True, sampler_index: int = None, script_args: list = None, enable_custom_k_sched: bool = False, k_sched_type: str = "", sigma_min: float=0.0, sigma_max: float=0.0, rho: float=0.0):
|
||||
def __init__(self, sd_model=None, outpath_samples=None, outpath_grids=None, prompt: str = "", styles: List[str] = None, seed: int = -1, subseed: int = -1, subseed_strength: float = 0, seed_resize_from_h: int = -1, seed_resize_from_w: int = -1, seed_enable_extras: bool = True, sampler_name: str = None, batch_size: int = 1, n_iter: int = 1, steps: int = 50, cfg_scale: float = 7.0, width: int = 512, height: int = 512, restore_faces: bool = False, tiling: bool = False, do_not_save_samples: bool = False, do_not_save_grid: bool = False, extra_generation_params: Dict[Any, Any] = None, overlay_images: Any = None, negative_prompt: str = None, eta: float = None, do_not_reload_embeddings: bool = False, denoising_strength: float = 0, ddim_discretize: str = None, s_min_uncond: float = 0.0, s_churn: float = 0.0, s_tmax: float = None, s_tmin: float = 0.0, s_noise: float = 1.0, override_settings: Dict[str, Any] = None, override_settings_restore_afterwards: bool = True, sampler_index: int = None, script_args: list = None):
|
||||
if sampler_index is not None:
|
||||
print("sampler_index argument for StableDiffusionProcessing does not do anything; use sampler_name", file=sys.stderr)
|
||||
|
||||
@ -146,11 +146,6 @@ class StableDiffusionProcessing:
|
||||
self.s_tmin = s_tmin or opts.s_tmin
|
||||
self.s_tmax = s_tmax or float('inf') # not representable as a standard ui option
|
||||
self.s_noise = s_noise or opts.s_noise
|
||||
self.enable_custom_k_sched = opts.custom_k_sched
|
||||
self.k_sched_type = k_sched_type or opts.k_sched_type
|
||||
self.sigma_max = sigma_max or opts.sigma_max
|
||||
self.sigma_min = sigma_min or opts.sigma_min
|
||||
self.rho = rho or opts.rho
|
||||
self.override_settings = {k: v for k, v in (override_settings or {}).items() if k not in shared.restricted_opts}
|
||||
self.override_settings_restore_afterwards = override_settings_restore_afterwards
|
||||
self.is_using_inpainting_conditioning = False
|
||||
@ -560,18 +555,9 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
|
||||
if uses_ensd:
|
||||
uses_ensd = sd_samplers_common.is_sampler_using_eta_noise_seed_delta(p)
|
||||
|
||||
# avoid loop import
|
||||
from modules import sd_samplers_kdiffusion
|
||||
use_custom_k_sched = p.enable_custom_k_sched and p.sampler_name in sd_samplers_kdiffusion.k_diffusion_samplers_map
|
||||
|
||||
generation_params = {
|
||||
"Steps": p.steps,
|
||||
"Sampler": p.sampler_name,
|
||||
"Enable Custom KDiffusion Schedule": use_custom_k_sched or None,
|
||||
"KDiffusion Scheduler Type": p.k_sched_type if use_custom_k_sched else None,
|
||||
"KDiffusion Scheduler sigma_max": p.sigma_max if use_custom_k_sched else None,
|
||||
"KDiffusion Scheduler sigma_min": p.sigma_min if use_custom_k_sched else None,
|
||||
"KDiffusion Scheduler rho": p.rho if use_custom_k_sched else None,
|
||||
"CFG scale": p.cfg_scale,
|
||||
"Image CFG scale": getattr(p, 'image_cfg_scale', None),
|
||||
"Seed": all_seeds[index],
|
||||
|
||||
@ -295,6 +295,13 @@ class KDiffusionSampler:
|
||||
|
||||
k_diffusion.sampling.torch = TorchHijack(self.sampler_noises if self.sampler_noises is not None else [])
|
||||
|
||||
if opts.custom_k_sched:
|
||||
p.extra_generation_params["Enable Custom KDiffusion Schedule"] = True
|
||||
p.extra_generation_params["KDiffusion Scheduler Type"] = opts.k_sched_type
|
||||
p.extra_generation_params["KDiffusion Scheduler sigma_max"] = opts.sigma_max
|
||||
p.extra_generation_params["KDiffusion Scheduler sigma_min"] = opts.sigma_min
|
||||
p.extra_generation_params["KDiffusion Scheduler rho"] = opts.rho
|
||||
|
||||
extra_params_kwargs = {}
|
||||
for param_name in self.extra_params:
|
||||
if hasattr(p, param_name) and param_name in inspect.signature(self.func).parameters:
|
||||
@ -318,15 +325,15 @@ class KDiffusionSampler:
|
||||
|
||||
if p.sampler_noise_scheduler_override:
|
||||
sigmas = p.sampler_noise_scheduler_override(steps)
|
||||
elif p.enable_custom_k_sched:
|
||||
elif opts.custom_k_sched:
|
||||
sigma_min, sigma_max = (0.1, 10) if opts.use_old_karras_scheduler_sigmas else (self.model_wrap.sigmas[0].item(), self.model_wrap.sigmas[-1].item())
|
||||
sigmas_func = k_diffusion_scheduler[p.k_sched_type]
|
||||
sigmas_func = k_diffusion_scheduler[opts.k_sched_type]
|
||||
sigmas_kwargs = {
|
||||
'sigma_min': p.sigma_min or sigma_min,
|
||||
'sigma_max': p.sigma_max or sigma_max
|
||||
'sigma_min': opts.sigma_min or sigma_min,
|
||||
'sigma_max': opts.sigma_max or sigma_max
|
||||
}
|
||||
if p.k_sched_type != 'exponential':
|
||||
sigmas_kwargs['rho'] = p.rho
|
||||
if opts.k_sched_type != 'exponential':
|
||||
sigmas_kwargs['rho'] = opts.rho
|
||||
sigmas = sigmas_func(n=steps, **sigmas_kwargs, device=shared.device)
|
||||
elif self.config is not None and self.config.options.get('scheduler', None) == 'karras':
|
||||
sigma_min, sigma_max = (0.1, 10) if opts.use_old_karras_scheduler_sigmas else (self.model_wrap.sigmas[0].item(), self.model_wrap.sigmas[-1].item())
|
||||
|
||||
Loading…
Reference in New Issue
Block a user