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Update nodes.py

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kijai 2024-08-29 19:15:38 +03:00
parent d02a3bf46f
commit 326d5945b7
1 changed files with 10 additions and 5 deletions
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15
nodes/nodes.py
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@ -1761,19 +1761,24 @@ class CheckpointPerturbWeights:
class DifferentialDiffusionAdvanced(): class DifferentialDiffusionAdvanced():
@classmethod @classmethod
def INPUT_TYPES(s): def INPUT_TYPES(s):
return {"required": {"model": ("MODEL", ), return {"required": {
"multiplier": ("FLOAT", {"default": 1.0, "min": -10.0, "max": 10.0, "step": 0.001}), "model": ("MODEL", ),
"samples": ("LATENT",),
"mask": ("MASK",),
"multiplier": ("FLOAT", {"default": 1.0, "min": -10.0, "max": 10.0, "step": 0.001}),
}} }}
RETURN_TYPES = ("MODEL",) RETURN_TYPES = ("MODEL", "LATENT")
FUNCTION = "apply" FUNCTION = "apply"
CATEGORY = "_for_testing" CATEGORY = "_for_testing"
INIT = False INIT = False
def apply(self, model, multiplier): def apply(self, model, samples, mask, multiplier):
self.multiplier = multiplier self.multiplier = multiplier
model = model.clone() model = model.clone()
model.set_model_denoise_mask_function(self.forward) model.set_model_denoise_mask_function(self.forward)
return (model,) s = samples.copy()
s["noise_mask"] = mask.reshape((-1, 1, mask.shape[-2], mask.shape[-1]))
return (model, s)
def forward(self, sigma: torch.Tensor, denoise_mask: torch.Tensor, extra_options: dict): def forward(self, sigma: torch.Tensor, denoise_mask: torch.Tensor, extra_options: dict):
model = extra_options["model"] model = extra_options["model"]