Spaces:
Runtime error
Runtime error
File size: 1,510 Bytes
ac6acf2 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 |
import torch
class InstructPixToPixConditioning:
@classmethod
def INPUT_TYPES(s):
return {"required": {"positive": ("CONDITIONING", ),
"negative": ("CONDITIONING", ),
"vae": ("VAE", ),
"pixels": ("IMAGE", ),
}}
RETURN_TYPES = ("CONDITIONING","CONDITIONING","LATENT")
RETURN_NAMES = ("positive", "negative", "latent")
FUNCTION = "encode"
CATEGORY = "conditioning/instructpix2pix"
def encode(self, positive, negative, pixels, vae):
x = (pixels.shape[1] // 8) * 8
y = (pixels.shape[2] // 8) * 8
if pixels.shape[1] != x or pixels.shape[2] != y:
x_offset = (pixels.shape[1] % 8) // 2
y_offset = (pixels.shape[2] % 8) // 2
pixels = pixels[:,x_offset:x + x_offset, y_offset:y + y_offset,:]
concat_latent = vae.encode(pixels)
out_latent = {}
out_latent["samples"] = torch.zeros_like(concat_latent)
out = []
for conditioning in [positive, negative]:
c = []
for t in conditioning:
d = t[1].copy()
d["concat_latent_image"] = concat_latent
n = [t[0], d]
c.append(n)
out.append(c)
return (out[0], out[1], out_latent)
NODE_CLASS_MAPPINGS = {
"InstructPixToPixConditioning": InstructPixToPixConditioning,
}
|