diff options
Diffstat (limited to 'modules/sd_samplers_kdiffusion.py')
| -rw-r--r-- | modules/sd_samplers_kdiffusion.py | 24 |
1 files changed, 16 insertions, 8 deletions
diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py index 3aee4e3a..46da0a97 100644 --- a/modules/sd_samplers_kdiffusion.py +++ b/modules/sd_samplers_kdiffusion.py @@ -87,8 +87,9 @@ class CFGDenoiser(torch.nn.Module): negative prompt.
"""
- def __init__(self):
+ def __init__(self, sampler):
super().__init__()
+ self.sampler = sampler
self.model_wrap = None
self.mask = None
self.nmask = None
@@ -126,11 +127,17 @@ class CFGDenoiser(torch.nn.Module): def update_inner_model(self):
self.model_wrap = None
+ c, uc = self.p.get_conds()
+ self.sampler.sampler_extra_args['cond'] = c
+ self.sampler.sampler_extra_args['uncond'] = uc
+
def forward(self, x, sigma, uncond, cond, cond_scale, s_min_uncond, image_cond):
if state.interrupted or state.skipped:
raise sd_samplers_common.InterruptedException
- sd_samplers_common.apply_refiner(self)
+ if sd_samplers_common.apply_refiner(self):
+ cond = self.sampler.sampler_extra_args['cond']
+ uncond = self.sampler.sampler_extra_args['uncond']
# at self.image_cfg_scale == 1.0 produced results for edit model are the same as with normal sampling,
# so is_edit_model is set to False to support AND composition.
@@ -282,12 +289,12 @@ class TorchHijack: class KDiffusionSampler:
def __init__(self, funcname, sd_model):
-
self.p = None
self.funcname = funcname
self.func = funcname if callable(funcname) else getattr(k_diffusion.sampling, self.funcname)
self.extra_params = sampler_extra_params.get(funcname, [])
- self.model_wrap_cfg = CFGDenoiser()
+ self.sampler_extra_args = {}
+ self.model_wrap_cfg = CFGDenoiser(self)
self.model_wrap = self.model_wrap_cfg.inner_model
self.sampler_noises = None
self.stop_at = None
@@ -476,7 +483,7 @@ class KDiffusionSampler: self.model_wrap_cfg.init_latent = x
self.last_latent = x
- extra_args = {
+ self.sampler_extra_args = {
'cond': conditioning,
'image_cond': image_conditioning,
'uncond': unconditional_conditioning,
@@ -484,7 +491,7 @@ class KDiffusionSampler: 's_min_uncond': self.s_min_uncond
}
- samples = self.launch_sampling(t_enc + 1, lambda: self.func(self.model_wrap_cfg, xi, extra_args=extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
+ samples = self.launch_sampling(t_enc + 1, lambda: self.func(self.model_wrap_cfg, xi, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
if self.model_wrap_cfg.padded_cond_uncond:
p.extra_generation_params["Pad conds"] = True
@@ -514,13 +521,14 @@ class KDiffusionSampler: extra_params_kwargs['noise_sampler'] = noise_sampler
self.last_latent = x
- samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args={
+ self.sampler_extra_args = {
'cond': conditioning,
'image_cond': image_conditioning,
'uncond': unconditional_conditioning,
'cond_scale': p.cfg_scale,
's_min_uncond': self.s_min_uncond
- }, disable=False, callback=self.callback_state, **extra_params_kwargs))
+ }
+ samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
if self.model_wrap_cfg.padded_cond_uncond:
p.extra_generation_params["Pad conds"] = True
|