threshold-negator4bit

4-bit bitwise NOT (one's complement negation).

Function

negator4bit(a3, a2, a1, a0) = [NOT(a3), NOT(a2), NOT(a1), NOT(a0)]

Inverts each bit independently.

Truth Table (selected rows)

Input	Output
0000	1111
0001	1110
0101	1010
1111	0000

Architecture

Single layer with 4 independent NOT neurons.

Output	Weight on input	Bias
y3	a3: -1	0
y2	a2: -1	0
y1	a1: -1	0
y0	a0: -1	0

Each neuron fires when its input is 0.

Parameters

Inputs	4
Outputs	4
Neurons	4
Layers	1
Parameters	8
Magnitude	4

Usage

from safetensors.torch import load_file
import torch

w = load_file('model.safetensors')

def negator4(a3, a2, a1, a0):
    inp = torch.tensor([float(a3), float(a2), float(a1), float(a0)])
    return [int((inp * w[f'y{i}.weight']).sum() + w[f'y{i}.bias'] >= 0)
            for i in range(4)]

print(negator4(0, 1, 0, 1))  # [1, 0, 1, 0]

License

MIT