Use automatic instead of None/default

1 files changed, 3 insertions, 3 deletions

diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py
index eff2e32d..a4c797c6 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/modules/sd_samplers_kdiffusion.py
@@ -46,7 +46,7 @@ sampler_extra_params = {
 

 k_diffusion_samplers_map = {x.name: x for x in samplers_data_k_diffusion}

 k_diffusion_scheduler = {

-    'None': None,

+    'Automatic': None,

     'karras': k_diffusion.sampling.get_sigmas_karras,

     'exponential': k_diffusion.sampling.get_sigmas_exponential,

     '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 [])

 

-        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 sigma_max"] = opts.sigma_max

             p.extra_generation_params["KDiffusion Scheduler sigma_min"] = opts.sigma_min

@@ -325,7 +325,7 @@ class KDiffusionSampler:
 

         if p.sampler_noise_scheduler_override:

             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())

             sigmas_func = k_diffusion_scheduler[opts.k_sched_type]

             sigmas_kwargs = {