metadata
license: mit
tags:
- pytorch
- safetensors
- threshold-logic
- neuromorphic
- modular-arithmetic
threshold-mod9
Trivial case: computes Hamming weight mod 9 for 8-bit inputs. Since max HW is 8 < 9, this is just HW.
Circuit
x₀ x₁ x₂ x₃ x₄ x₅ x₆ x₇
│ │ │ │ │ │ │ │
│ │ │ │ │ │ │ │
w: 1 1 1 1 1 1 1 1
└──┴──┴──┴──┼──┴──┴──┴──┘
▼
┌─────────┐
│ b: 0 │
└─────────┘
│
▼
HW (= HW mod 9)
Why Trivial?
For mod m where m > (number of inputs), no reset ever occurs:
- 8 inputs → max HW = 8
- 8 mod 9 = 8 (no wraparound)
The circuit just sums the inputs. It's a degenerate case included for completeness of the MOD-m family.
Parameters
| Weights | [1, 1, 1, 1, 1, 1, 1, 1] |
| Bias | 0 |
| Total | 9 parameters |
Usage
from safetensors.torch import load_file
import torch
w = load_file('model.safetensors')
def mod9(bits): # Actually just HW
inputs = torch.tensor([float(b) for b in bits])
return int((inputs * w['weight']).sum() + w['bias'])
Files
threshold-mod9/
├── model.safetensors
├── model.py
├── config.json
└── README.md
License
MIT