phanerozoic/threshold-comparator8bit
010
threshold-comparator8bit
8-bit magnitude comparator. Compares two 8-bit unsigned values.
Function
compare8(A, B) -> (GT, LT, EQ)
- GT = 1 if A > B
- LT = 1 if A < B
- EQ = 1 if A = B
Exactly one output is always active.
Architecture
A[7:0] B[7:0]
│ │
└───────┬───────┘
│
┌──────┴──────┐
│ │
▼ ▼
┌───┐ ┌───┐
│GT │ │LT │ Layer 1
│A-B│ │B-A│
│>=1│ │>=1│
└───┘ └───┘
│ │
└──────┬──────┘
│
▼
┌─────┐
│ EQ │ Layer 2
│ NOR │
└─────┘Uses positional weighting: treats inputs as binary numbers.
GT neuron: weights A bits positively (128,64,32,16,8,4,2,1), B bits negatively. Fires when weighted sum A - B >= 1.
LT neuron: opposite weights. Fires when B - A >= 1.
EQ neuron: NOR of GT and LT. Fires when both are zero.
Parameters
Truth Table (examples)
Usage
from safetensors.torch import load_file
import torch
w = load_file('model.safetensors')
def compare(a, b):
a_bits = [(a >> (7-i)) & 1 for i in range(8)]
b_bits = [(b >> (7-i)) & 1 for i in range(8)]
inp = torch.tensor([float(x) for x in a_bits + b_bits])
gt = int((inp @ w['gt.weight'].T + w['gt.bias'] >= 0).item())
lt = int((inp @ w['lt.weight'].T + w['lt.bias'] >= 0).item())
eq = int((torch.tensor([float(gt), float(lt)]) @ w['eq.weight'].T + w['eq.bias'] >= 0).item())
return gt, lt, eq
# compare(200, 100) = (1, 0, 0) # 200 > 100License
MIT