Latent Lerp (mtb)¶
Documentation¶
- Class name:
Latent Lerp (mtb)
- Category:
mtb/latent
- Output node:
False
Performs linear interpolation between two latent vectors, blending them based on a specified ratio to create a new latent vector.
Input types¶
Required¶
A
- The first latent vector to be interpolated.
- Comfy dtype:
LATENT
- Python dtype:
Dict[str, torch.Tensor]
B
- The second latent vector to be interpolated.
- Comfy dtype:
LATENT
- Python dtype:
Dict[str, torch.Tensor]
t
- The interpolation ratio, determining the blend between the two latent vectors.
- Comfy dtype:
FLOAT
- Python dtype:
float
Output types¶
latent
- Comfy dtype:
LATENT
- The resulting latent vector after interpolation.
- Python dtype:
Tuple[Dict[str, torch.Tensor]]
- Comfy dtype:
Usage tips¶
- Infra type:
GPU
- Common nodes: unknown
Source code¶
class MTB_LatentLerp:
"""Linear interpolation (blend) between two latent vectors"""
@classmethod
def INPUT_TYPES(cls):
return {
"required": {
"A": ("LATENT",),
"B": ("LATENT",),
"t": (
"FLOAT",
{"default": 0.5, "min": 0.0, "max": 1.0, "step": 0.01},
),
}
}
RETURN_TYPES = ("LATENT",)
FUNCTION = "lerp_latent"
CATEGORY = "mtb/latent"
def lerp_latent(self, A, B, t):
a = A.copy()
b = B.copy()
torch.lerp(a["samples"], b["samples"], t, out=a["samples"])
return (a,)