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Use automatic instead of None/default

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This commit is contained in:
Kohaku-Blueleaf 2023-05-24 00:18:09 +08:00
parent 27962ded4a
commit 1601fccebc
2 changed files with 4 additions and 4 deletions
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6
modules/sd_samplers_kdiffusion.py
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@ -46,7 +46,7 @@ sampler_extra_params = {
k_diffusion_samplers_map = {x.name: x for x in samplers_data_k_diffusion} k_diffusion_samplers_map = {x.name: x for x in samplers_data_k_diffusion}
k_diffusion_scheduler = { k_diffusion_scheduler = {
'None': None, 'Automatic': None,
'karras': k_diffusion.sampling.get_sigmas_karras, 'karras': k_diffusion.sampling.get_sigmas_karras,
'exponential': k_diffusion.sampling.get_sigmas_exponential, 'exponential': k_diffusion.sampling.get_sigmas_exponential,
'polyexponential': k_diffusion.sampling.get_sigmas_polyexponential 'polyexponential': k_diffusion.sampling.get_sigmas_polyexponential
@ -296,7 +296,7 @@ class KDiffusionSampler:
k_diffusion.sampling.torch = TorchHijack(self.sampler_noises if self.sampler_noises is not None else []) k_diffusion.sampling.torch = TorchHijack(self.sampler_noises if self.sampler_noises is not None else [])
if opts.k_sched_type != "None": if opts.k_sched_type != "Automatic":
p.extra_generation_params["KDiffusion Scheduler Type"] = opts.k_sched_type 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_max"] = opts.sigma_max
p.extra_generation_params["KDiffusion Scheduler sigma_min"] = opts.sigma_min p.extra_generation_params["KDiffusion Scheduler sigma_min"] = opts.sigma_min
@ -325,7 +325,7 @@ class KDiffusionSampler:
if p.sampler_noise_scheduler_override: if p.sampler_noise_scheduler_override:
sigmas = p.sampler_noise_scheduler_override(steps) sigmas = p.sampler_noise_scheduler_override(steps)
elif opts.k_sched_type != "None": elif opts.k_sched_type != "Automatic":
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()) 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[opts.k_sched_type] sigmas_func = k_diffusion_scheduler[opts.k_sched_type]
sigmas_kwargs = { sigmas_kwargs = {

2
modules/shared.py
View File

@ -517,7 +517,7 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters"
's_churn': OptionInfo(0.0, "sigma churn", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), 's_churn': OptionInfo(0.0, "sigma churn", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
's_tmin': OptionInfo(0.0, "sigma tmin", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}), '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}), 's_noise': OptionInfo(1.0, "sigma noise", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
'k_sched_type': OptionInfo("default", "scheduler type", gr.Dropdown, {"choices": ["None", "karras", "exponential", "polyexponential"]}), 'k_sched_type': OptionInfo("Automatic", "scheduler type", gr.Dropdown, {"choices": ["Automatic", "karras", "exponential", "polyexponential"]}),
'sigma_max': OptionInfo(0.0, "sigma max", gr.Number).info("the maximum noise strength for the scheduler. Set to 0 to use the same value which 'xxx karras' samplers use."), 'sigma_max': OptionInfo(0.0, "sigma max", gr.Number).info("the maximum noise strength for the scheduler. Set to 0 to use the same value which 'xxx karras' samplers use."),
'sigma_min': OptionInfo(0.0, "sigma min", gr.Number).info("the minimum noise strength for the scheduler. Set to 0 to use the same value which 'xxx karras' samplers use."), 'sigma_min': OptionInfo(0.0, "sigma min", gr.Number).info("the minimum noise strength for the scheduler. Set to 0 to use the same value which 'xxx karras' samplers use."),
'rho': OptionInfo(7.0, "rho", gr.Number).info("higher will make a more steep noise scheduler (decrease faster). default for karras is 7.0, for polyexponential is 1.0"), 'rho': OptionInfo(7.0, "rho", gr.Number).info("higher will make a more steep noise scheduler (decrease faster). default for karras is 7.0, for polyexponential is 1.0"),