diff options
| -rw-r--r-- | modules/sd_samplers_cfg_denoiser.py | 34 | ||||
| -rw-r--r-- | modules/sd_samplers_common.py | 1 |
2 files changed, 17 insertions, 18 deletions
diff --git a/modules/sd_samplers_cfg_denoiser.py b/modules/sd_samplers_cfg_denoiser.py index a700e692..f13e8dcc 100644 --- a/modules/sd_samplers_cfg_denoiser.py +++ b/modules/sd_samplers_cfg_denoiser.py @@ -6,7 +6,6 @@ import modules.shared as shared from modules.script_callbacks import CFGDenoiserParams, cfg_denoiser_callback
from modules.script_callbacks import CFGDenoisedParams, cfg_denoised_callback
from modules.script_callbacks import AfterCFGCallbackParams, cfg_after_cfg_callback
-import modules.soft_inpainting as si
def catenate_conds(conds):
@@ -44,7 +43,6 @@ class CFGDenoiser(torch.nn.Module): self.model_wrap = None
self.mask = None
self.nmask = None
- self.soft_inpainting: si.SoftInpaintingParameters = None
self.init_latent = None
self.steps = None
"""number of steps as specified by user in UI"""
@@ -94,7 +92,6 @@ class CFGDenoiser(torch.nn.Module): 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
@@ -111,15 +108,24 @@ class CFGDenoiser(torch.nn.Module): assert not is_edit_model or all(len(conds) == 1 for conds in conds_list), "AND is not supported for InstructPix2Pix checkpoint (unless using Image CFG scale = 1.0)"
+ # If we use masks, blending between the denoised and original latent images occurs here.
+ def apply_blend(latent):
+ if hasattr(self.p, "denoiser_masked_blend_function") and callable(self.p.denoiser_masked_blend_function):
+ return self.p.denoiser_masked_blend_function(
+ self,
+ # Using an argument dictionary so that arguments can be added without breaking extensions.
+ args=
+ {
+ "denoiser": self,
+ "current_latent": latent,
+ "sigma": sigma
+ })
+ else:
+ return self.init_latent * self.mask + self.nmask * latent
+
# Blend in the original latents (before)
if self.mask_before_denoising and self.mask is not None:
- if self.soft_inpainting is None:
- x = self.init_latent * self.mask + self.nmask * x
- else:
- x = si.latent_blend(self.soft_inpainting,
- self.init_latent,
- x,
- si.get_modified_nmask(self.soft_inpainting, self.nmask, sigma))
+ x = apply_blend(x)
batch_size = len(conds_list)
repeats = [len(conds_list[i]) for i in range(batch_size)]
@@ -222,13 +228,7 @@ class CFGDenoiser(torch.nn.Module): # Blend in the original latents (after)
if not self.mask_before_denoising and self.mask is not None:
- if self.soft_inpainting is None:
- denoised = self.init_latent * self.mask + self.nmask * denoised
- else:
- denoised = si.latent_blend(self.soft_inpainting,
- self.init_latent,
- denoised,
- si.get_modified_nmask(self.soft_inpainting, self.nmask, sigma))
+ denoised = apply_blend(denoised)
self.sampler.last_latent = self.get_pred_x0(torch.cat([x_in[i:i + 1] for i in denoised_image_indexes]), torch.cat([x_out[i:i + 1] for i in denoised_image_indexes]), sigma)
diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py index 9682bee3..58efcad2 100644 --- a/modules/sd_samplers_common.py +++ b/modules/sd_samplers_common.py @@ -277,7 +277,6 @@ class Sampler: self.model_wrap_cfg.p = p
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.soft_inpainting = p.soft_inpainting if hasattr(p, 'soft_inpainting') else None
self.model_wrap_cfg.step = 0
self.model_wrap_cfg.image_cfg_scale = getattr(p, 'image_cfg_scale', None)
self.eta = p.eta if p.eta is not None else getattr(opts, self.eta_option_field, 0.0)
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