        a1    a0
        │     │
    ┌───┴─────┴───┐
    │             │
    ▼   ▼   ▼   ▼
  ┌───┬───┬───┬───┐
  │y3 │y2 │y1 │y0 │  Layer 1
  │AND│A·B│A·B│NOR│
  └───┴───┴───┴───┘
    │   │   │   │
    ▼   ▼   ▼   ▼

Each output is a single threshold neuron:

y0 = NOR(a1, a0): w=[-1,-1], b=0
y1 = NOT(a1) AND a0: w=[-1,1], b=-1
y2 = a1 AND NOT(a0): w=[1,-1], b=-1
y3 = a1 AND a0: w=[1,1], b=-2

Parameters


Inputs	2
Outputs	4
Neurons	4
Layers	1
Parameters	12
Magnitude	12

Usage

python

from safetensors.torch import load_file
import torch

w = load_file('model.safetensors')

def onehot(a1, a0):
    inp = torch.tensor([float(a1), float(a0)])
    y0 = int((inp @ w['y0.weight'].T + w['y0.bias'] >= 0).item())
    y1 = int((inp @ w['y1.weight'].T + w['y1.bias'] >= 0).item())
    y2 = int((inp @ w['y2.weight'].T + w['y2.bias'] >= 0).item())
    y3 = int((inp @ w['y3.weight'].T + w['y3.bias'] >= 0).item())
    return y3, y2, y1, y0

# onehot(1, 0) = (0, 1, 0, 0)  # value 2

Applications

Address decoding
Memory select lines
State machine encoding
Neural network input preprocessing

License

MIT

phanerozoic/threshold-onehot-encoder

threshold-onehot-encoder

Function

Truth Table

Architecture

Parameters

Usage

Applications

License

phanerozoic/
threshold-onehot-encoder