threshold-demux4

1:4 demultiplexer. Routes data input to one of 4 outputs based on 2-bit select.

Function

DEMUX4(d, s1, s0) -> [y0, y1, y2, y3]

yi = d AND (s == i), where s = 2*s1 + s0

Truth Table

d	s1	s0	y0	y1	y2	y3
0	0	0	0	0	0	0
0	0	1	0	0	0	0
0	1	0	0	0	0	0
0	1	1	0	0	0	0
1	0	0	1	0	0	0
1	0	1	0	1	0	0
1	1	0	0	0	1	0
1	1	1	0	0	0	1

Architecture

Single layer with 4 neurons. Each output yi fires when d=1 AND select matches i.

Output	Weights [d, s1, s0]	Bias
y0	[1, -1, -1]	-1
y1	[1, -1, +1]	-2
y2	[1, +1, -1]	-2
y3	[1, +1, +1]	-3

Parameters

Inputs	3 (1 data + 2 select)
Outputs	4
Neurons	4
Layers	1
Parameters	16
Magnitude	20

Usage

from safetensors.torch import load_file
import torch

w = load_file('model.safetensors')

def demux4(d, s1, s0):
    inp = torch.tensor([float(d), float(s1), float(s0)])
    return [int((inp * w[f'y{i}.weight']).sum() + w[f'y{i}.bias'] >= 0)
            for i in range(4)]

# Route d=1 to output 2 (s=10)
print(demux4(1, 1, 0))  # [0, 0, 1, 0]

License

MIT