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Use original CFGDenoiser if image_cfg_scale = 1

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If image_cfg_scale is =1 then the original image is not used for the output. We can then use the original CFGDenoiser to get the same result to support AND functionality.

Maybe in the future AND can be supported with "Image CFG Scale"
This commit is contained in:
Kyle 2023-02-03 19:46:13 -05:00
parent c27c0de0f7
commit ba6a4e7e94
1 changed files with 5 additions and 2 deletions
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7
modules/sd_samplers_kdiffusion.py
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@ -245,7 +245,7 @@ class KDiffusionSampler:
self.funcname = funcname
self.func = getattr(k_diffusion.sampling, self.funcname)
self.extra_params = sampler_extra_params.get(funcname, [])
self.model_wrap_cfg = CFGDenoiser(self.model_wrap) if not shared.sd_model.cond_stage_key == "edit" else CFGDenoiserEdit(self.model_wrap)
self.model_wrap_cfg = CFGDenoiser(self.model_wrap)
self.sampler_noises = None
self.stop_at = None
self.eta = None
@ -280,6 +280,9 @@ class KDiffusionSampler:
return p.steps
def initialize(self, p):
if shared.sd_model.cond_stage_key == "edit" and getattr(p, 'image_cfg_scale', None) != 1:
self.model_wrap_cfg = CFGDenoiserEdit(self.model_wrap)
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
@ -352,7 +355,7 @@ class KDiffusionSampler:
'cond_scale': p.cfg_scale,
}
if hasattr(p, 'image_cfg_scale'):
if hasattr(p, 'image_cfg_scale') and p.image_cfg_scale != 1 and p.image_cfg_scale != None:
extra_args['image_cfg_scale'] = p.image_cfg_scale
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))