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5 changes: 4 additions & 1 deletion modules/sd_samplers.py
Original file line number Diff line number Diff line change
Expand Up @@ -462,14 +462,17 @@ def initialize(self, p):
return extra_params_kwargs

def get_sigmas(self, p, steps):
disc = opts.always_discard_next_to_last_sigma or (self.config is not None and self.config.options.get('discard_next_to_last_sigma', False))
steps += 1 if disc else 0

if p.sampler_noise_scheduler_override:
sigmas = p.sampler_noise_scheduler_override(steps)
elif self.config is not None and self.config.options.get('scheduler', None) == 'karras':
sigmas = k_diffusion.sampling.get_sigmas_karras(n=steps, sigma_min=0.1, sigma_max=10, device=shared.device)
else:
sigmas = self.model_wrap.get_sigmas(steps)

if self.config is not None and self.config.options.get('discard_next_to_last_sigma', False):
if disc:
sigmas = torch.cat([sigmas[:-2], sigmas[-1:]])

return sigmas
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1 change: 1 addition & 0 deletions modules/shared.py
Original file line number Diff line number Diff line change
Expand Up @@ -418,6 +418,7 @@ def list_samplers():
's_tmin': OptionInfo(0.0, "sigma tmin", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}),
'always_discard_next_to_last_sigma': OptionInfo(False, "Always discard next-to-last sigma"),
}))

options_templates.update(options_section((None, "Hidden options"), {
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