diff options
| -rw-r--r-- | modules/generation_parameters_copypaste.py | 4 | ||||
| -rw-r--r-- | modules/sd_samplers_kdiffusion.py | 34 |
2 files changed, 37 insertions, 1 deletions
diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 593abfef..e71c9601 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -328,6 +328,10 @@ infotext_to_setting_name_mapping = [ ('Noise multiplier', 'initial_noise_multiplier'),
('Eta', 'eta_ancestral'),
('Eta DDIM', 'eta_ddim'),
+ ('Sigma churn', 's_churn'),
+ ('Sigma tmin', 's_tmin'),
+ ('Sigma tmax', 's_tmax'),
+ ('Sigma noise', 's_noise'),
('Discard penultimate sigma', 'always_discard_next_to_last_sigma'),
('UniPC variant', 'uni_pc_variant'),
('UniPC skip type', 'uni_pc_skip_type'),
diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index 8bb639f5..db71a549 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -4,6 +4,7 @@ import inspect import k_diffusion.sampling
from modules import prompt_parser, devices, sd_samplers_common, sd_samplers_extra
+from modules.processing import StableDiffusionProcessing
from modules.shared import opts, state
import modules.shared as shared
from modules.script_callbacks import CFGDenoiserParams, cfg_denoiser_callback
@@ -280,6 +281,14 @@ class KDiffusionSampler: self.last_latent = None
self.s_min_uncond = None
+ # NOTE: These are also defined in the StableDiffusionProcessing class.
+ # They should have been here to begin with but we're going to
+ # leave that class __init__ signature alone.
+ self.s_churn = 0.0
+ self.s_tmin = 0.0
+ self.s_tmax = float('inf')
+ self.s_noise = 1.0
+
self.conditioning_key = sd_model.model.conditioning_key
def callback_state(self, d):
@@ -314,7 +323,7 @@ class KDiffusionSampler: def number_of_needed_noises(self, p):
return p.steps
- def initialize(self, p):
+ def initialize(self, p: StableDiffusionProcessing):
self.model_wrap_cfg.mask = p.mask if hasattr(p, 'mask') else None
self.model_wrap_cfg.nmask = p.nmask if hasattr(p, 'nmask') else None
self.model_wrap_cfg.step = 0
@@ -335,6 +344,29 @@ class KDiffusionSampler: extra_params_kwargs['eta'] = self.eta
+ if len(self.extra_params) > 0:
+ s_churn = getattr(opts, 's_churn', p.s_churn)
+ s_tmin = getattr(opts, 's_tmin', p.s_tmin)
+ s_tmax = getattr(opts, 's_tmax', p.s_tmax) or self.s_tmax # 0 = inf
+ s_noise = getattr(opts, 's_noise', p.s_noise)
+
+ if s_churn != self.s_churn:
+ extra_params_kwargs['s_churn'] = s_churn
+ p.s_churn = s_churn
+ p.extra_generation_params['Sigma churn'] = s_churn
+ if s_tmin != self.s_tmin:
+ extra_params_kwargs['s_tmin'] = s_tmin
+ p.s_tmin = s_tmin
+ p.extra_generation_params['Sigma tmin'] = s_tmin
+ if s_tmax != self.s_tmax:
+ extra_params_kwargs['s_tmax'] = s_tmax
+ p.s_tmax = s_tmax
+ p.extra_generation_params['Sigma tmax'] = s_tmax
+ if s_noise != self.s_noise:
+ extra_params_kwargs['s_noise'] = s_noise
+ p.s_noise = s_noise
+ p.extra_generation_params['Sigma noise'] = s_noise
+
return extra_params_kwargs
def get_sigmas(self, p, steps):
|