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

# threshold-nand4

4-input NAND gate. Outputs 0 only when all inputs are 1.

## Circuit

```
  x1  x2  x3  x4
   │   │   │   │
   └───┴───┴───┘
         │
         ▼
    ┌──────────┐
    │w:-1,-1,-1,-1│
    │ b: 3     │
    └──────────┘
         │
         ▼
  NAND4(x1,x2,x3,x4)
```

## Parameters

| | |
|---|---|
| Weights | [-1, -1, -1, -1] |
| Bias | 3 |
| Magnitude | 7 |

## Optimality

Exhaustive enumeration of 7,183 configurations confirms magnitude 7 is optimal. 1 valid configuration exists.

| Magnitude | Valid Configs |
|-----------|---------------|
| 0-6 | 0 |
| 7 | 1 |

## Usage

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

w = load_file('model.safetensors')

def nand4(x1, x2, x3, x4):
    inputs = torch.tensor([float(x1), float(x2), float(x3), float(x4)])
    return int((inputs * w['weight']).sum() + w['bias'] >= 0)
```

## License

MIT