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import torch
class RegionalStyleModelApplyNode:
@classmethod
def INPUT_TYPES(s):
return {"required": {
"style_model": ("STYLE_MODEL", ),
"clip_vision_output": ("CLIP_VISION_OUTPUT", ),
"strength": ("FLOAT", {"default": 1, "min": -1000.0, "max": 1000.0, "step": 0.01, "round": 0.01}),
},
"optional": {
"conditioning": ("CONDITIONING", ),
}}
RETURN_TYPES = ("CONDITIONING",)
FUNCTION = "apply_stylemodel"
CATEGORY = "fluxtapoz"
def apply_stylemodel(self, clip_vision_output, style_model, strength, conditioning=None):
cond = style_model.get_cond(clip_vision_output).flatten(start_dim=0, end_dim=1).unsqueeze(dim=0) * strength
c = []
if conditioning is not None:
for t in conditioning:
n = [torch.cat((t[0], cond), dim=1), t[1].copy()]
c.append(n)
else:
c.append([cond, None])
return (c, )
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