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[pull] master from comfyanonymous:master #490

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Merged
pull merged 2 commits into from
Dec 20, 2025
Merged

[pull] master from comfyanonymous:master #490

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809ce68
Support nested tensor denoise masks. (#11431)
comfyanonymous Dec 20, 2025
514c24d
Fix error from logging line (#11423)
drozbay Dec 20, 2025
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2 changes: 1 addition & 1 deletion comfy/context_windows.py
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Original file line number Diff line number Diff line change
Expand Up @@ -143,7 +143,7 @@ def get_resized_cond(self, cond_in: list[dict], x_in: torch.Tensor, window: Inde
# if multiple conds, split based on primary region
if self.split_conds_to_windows and len(cond_in) > 1:
region = window.get_region_index(len(cond_in))
logging.info(f"Splitting conds to windows; using region {region} for window {window[0]}-{window[-1]} with center ratio {window.center_ratio:.3f}")
logging.info(f"Splitting conds to windows; using region {region} for window {window.index_list[0]}-{window.index_list[-1]} with center ratio {window.center_ratio:.3f}")
cond_in = [cond_in[region]]
# cond object is a list containing a dict - outer list is irrelevant, so just loop through it
for actual_cond in cond_in:
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21 changes: 18 additions & 3 deletions comfy/samplers.py
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Expand Up @@ -984,9 +984,6 @@ def outer_sample(self, noise, latent_image, sampler, sigmas, denoise_mask=None,
self.inner_model, self.conds, self.loaded_models = comfy.sampler_helpers.prepare_sampling(self.model_patcher, noise.shape, self.conds, self.model_options)
device = self.model_patcher.load_device

if denoise_mask is not None:
denoise_mask = comfy.sampler_helpers.prepare_mask(denoise_mask, noise.shape, device)

noise = noise.to(device)
latent_image = latent_image.to(device)
sigmas = sigmas.to(device)
Expand All @@ -1013,6 +1010,24 @@ def sample(self, noise, latent_image, sampler, sigmas, denoise_mask=None, callba
else:
latent_shapes = [latent_image.shape]

if denoise_mask is not None:
if denoise_mask.is_nested:
denoise_masks = denoise_mask.unbind()
denoise_masks = denoise_masks[:len(latent_shapes)]
else:
denoise_masks = [denoise_mask]

for i in range(len(denoise_masks), len(latent_shapes)):
denoise_masks.append(torch.ones(latent_shapes[i]))

for i in range(len(denoise_masks)):
denoise_masks[i] = comfy.sampler_helpers.prepare_mask(denoise_masks[i], latent_shapes[i], self.model_patcher.load_device)

if len(denoise_masks) > 1:
denoise_mask, _ = comfy.utils.pack_latents(denoise_masks)
else:
denoise_mask = denoise_masks[0]

self.conds = {}
for k in self.original_conds:
self.conds[k] = list(map(lambda a: a.copy(), self.original_conds[k]))
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