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import torch
from ..utils.latent_guide import LatentGuide
class AddLatentGuideNode:
@classmethod
def INPUT_TYPES(s):
return {"required": {"model": ("MODEL",),
"latent": ("LATENT",),
"image_latent": ("LATENT",),
"index": ("INT", {"default": 0, "min": -1, "max": 9999, "step": 1}),
"insert": ("BOOLEAN", { "default": False }),
}}
RETURN_TYPES = ("MODEL", "LATENT")
CATEGORY = "ltxtricks"
FUNCTION = "generate"
def generate(self, model, latent, image_latent, index, insert):
image_latent = image_latent['samples']
latent = latent['samples'].clone()
# Convert negative index to positive
if insert:
# Handle insertion
if index == 0:
# Insert at beginning
latent = torch.cat([image_latent[:,:,0:1], latent], dim=2)
elif index >= latent.shape[2] or index < 0:
# Append to end
latent = torch.cat([latent, image_latent[:,:,0:1]], dim=2)
else:
# Insert in middle
latent = torch.cat([
latent[:,:,:index],
image_latent[:,:,0:1],
latent[:,:,index:]
], dim=2)
else:
# Original replacement behavior
latent[:,:,index] = image_latent[:,:,0]
model = model.clone()
guiding_latent = LatentGuide(image_latent, index)
model.set_model_patch(guiding_latent, 'guiding_latents')
return (model, {"samples": latent}, )
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