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improvements 

See:
https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/10649#issuecomment-1561047723
This commit is contained in:
Kohaku-Blueleaf 2023-05-24 20:35:58 +08:00
parent 1601fccebc
commit 4b88e24ebe
4 changed files with 39 additions and 20 deletions
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20
modules/generation_parameters_copypaste.py
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@ -306,6 +306,18 @@ Steps: 20, Sampler: Euler a, CFG scale: 7, Seed: 965400086, Size: 512x512, Model
if "RNG" not in res:
res["RNG"] = "GPU"
if "KDiff Sched Type" not in res:
res["KDiff Sched Type"] = "Automatic"
if "KDiff Sched max sigma" not in res:
res["KDiff Sched max sigma"] = 14.6
if "KDiff Sched min sigma" not in res:
res["KDiff Sched min sigma"] = 0.3
if "KDiff Sched rho" not in res:
res["KDiff Sched rho"] = 7.0
return res
@ -318,10 +330,10 @@ infotext_to_setting_name_mapping = [
('Conditional mask weight', 'inpainting_mask_weight'),
('Model hash', 'sd_model_checkpoint'),
('ENSD', 'eta_noise_seed_delta'),
('KDiffusion Scheduler Type', 'k_sched_type'),
('KDiffusion Scheduler sigma_max', 'sigma_max'),
('KDiffusion Scheduler sigma_min', 'sigma_min'),
('KDiffusion Scheduler rho', 'rho'),
('KDiff Sched Type', 'k_sched_type'),
('KDiff Sched max sigma', 'sigma_max'),
('KDiff Sched min sigma', 'sigma_min'),
('KDiff Sched rho', 'rho'),
('Noise multiplier', 'initial_noise_multiplier'),
('Eta', 'eta_ancestral'),
('Eta DDIM', 'eta_ddim'),

27
modules/sd_samplers_kdiffusion.py
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@ -296,12 +296,6 @@ class KDiffusionSampler:
k_diffusion.sampling.torch = TorchHijack(self.sampler_noises if self.sampler_noises is not None else [])
if opts.k_sched_type != "Automatic":
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:
@ -326,14 +320,27 @@ class KDiffusionSampler:
if p.sampler_noise_scheduler_override:
sigmas = p.sampler_noise_scheduler_override(steps)
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())
sigmas_func = k_diffusion_scheduler[opts.k_sched_type]
m_sigma_min, m_sigma_max = (self.model_wrap.sigmas[0].item(), self.model_wrap.sigmas[-1].item())
sigma_min, sigma_max = (0.1, 10)
sigmas_kwargs = {
'sigma_min': opts.sigma_min or sigma_min,
'sigma_max': opts.sigma_max or sigma_max
'sigma_min': sigma_min if opts.use_old_karras_scheduler_sigmas else m_sigma_min,
'sigma_max': sigma_max if opts.use_old_karras_scheduler_sigmas else m_sigma_max
}
sigmas_func = k_diffusion_scheduler[opts.k_sched_type]
p.extra_generation_params["KDiff Sched Type"] = opts.k_sched_type
if opts.sigma_min != 0.3:
# take 0.0 as model default
sigmas_kwargs['sigma_min'] = opts.sigma_min or m_sigma_min
p.extra_generation_params["KDiff Sched min sigma"] = opts.sigma_min
if opts.sigma_max != 14.6:
sigmas_kwargs['sigma_max'] = opts.sigma_max or m_sigma_max
p.extra_generation_params["KDiff Sched max sigma"] = opts.sigma_max
if opts.k_sched_type != 'exponential':
sigmas_kwargs['rho'] = opts.rho
p.extra_generation_params["KDiff Sched 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())

4
modules/shared.py
View File

@ -518,8 +518,8 @@ options_templates.update(options_section(('sampler-params', "Sampler parameters"
'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}),
'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_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_max': OptionInfo(14.6, "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(0.3, "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"),
'eta_noise_seed_delta': OptionInfo(0, "Eta noise seed delta", gr.Number, {"precision": 0}).info("ENSD; does not improve anything, just produces different results for ancestral samplers - only useful for reproducing images"),
'always_discard_next_to_last_sigma': OptionInfo(False, "Always discard next-to-last sigma").link("PR", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/6044"),

8
scripts/xyz_grid.py
View File

@ -220,10 +220,10 @@ axis_options = [
AxisOption("Sigma min", float, apply_field("s_tmin")),
AxisOption("Sigma max", float, apply_field("s_tmax")),
AxisOption("Sigma noise", float, apply_field("s_noise")),
AxisOption("KDiffusion Scheduler Type", str, apply_override("k_sched_type"), choices=lambda: list(sd_samplers_kdiffusion.k_diffusion_scheduler)),
AxisOption("KDiffusion Scheduler Sigma Min", float, apply_override("sigma_min")),
AxisOption("KDiffusion Scheduler Sigma Max", float, apply_override("sigma_max")),
AxisOption("KDiffusion Scheduler rho", float, apply_override("rho")),
AxisOption("KDiff Sched Type", str, apply_override("k_sched_type"), choices=lambda: list(sd_samplers_kdiffusion.k_diffusion_scheduler)),
AxisOption("KDiff Sched min sigma", float, apply_override("sigma_min")),
AxisOption("KDiff Sched max sigma", float, apply_override("sigma_max")),
AxisOption("KDiff Sched rho", float, apply_override("rho")),
AxisOption("Eta", float, apply_field("eta")),
AxisOption("Clip skip", int, apply_clip_skip),
AxisOption("Denoising", float, apply_field("denoising_strength")),