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Support nested tensor denoise masks. (#11431)

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comfyanonymous 2025-12-19 16:59:25 -08:00 committed by GitHub
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commit 809ce68749
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1 changed files with 18 additions and 3 deletions
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comfy/samplers.py
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@ -984,9 +984,6 @@ class CFGGuider:
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)
@ -1013,6 +1010,24 @@ class CFGGuider:
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]))