improvements

See:
https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/10649#issuecomment-1561047723

1 files changed, 17 insertions, 10 deletions

diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py
index a4c797c6..d2d172e4 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -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())