---
license: mit
tags:
- pytorch
- safetensors
- threshold-logic
- neuromorphic
---

# threshold-or

A 1-of-2 threshold gate. One active input is enough to fire.

## Circuit

```
    x   y
    │   │
    └─┬─┘
      ▼
  ┌───────┐
  │ w: 1,1│
  │ b: -1 │
  └───────┘
      │
      ▼
   OR(x,y)
```

## Mechanism

Same weights as AND, but bias -1 instead of -2. The lower bar means a single vote suffices:

| x | y | sum | output |
|---|---|-----|--------|
| 0 | 0 | -1 | 0 |
| 0 | 1 | 0 | 1 |
| 1 | 0 | 0 | 1 |
| 1 | 1 | 1 | 1 |

AND and OR are the same circuit with different thresholds. This is the essence of threshold logic: the bias determines how many inputs must agree.

## Parameters

| | |
|---|---|
| Weights | [1, 1] |
| Bias | -1 |
| Total | 3 parameters |

## Optimality

Exhaustive enumeration of all 25 weight configurations at magnitudes 0-3 confirms this circuit is **already at minimum magnitude (3)**. There is exactly one valid configuration at magnitude 3, and no valid configurations exist below it.

## Properties

- Linearly separable
- De Morgan dual: OR(x,y) = NOT(AND(NOT(x), NOT(y)))
- Generalizes to n-input OR with weights all 1, bias -1

## Usage

```python
from safetensors.torch import load_file
import torch

w = load_file('model.safetensors')

def or_gate(x, y):
    inputs = torch.tensor([float(x), float(y)])
    return int((inputs * w['weight']).sum() + w['bias'] >= 0)
```

## Files

```
threshold-or/
├── model.safetensors
├── model.py
├── config.json
└── README.md
```

## License

MIT