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

# threshold-reverse4

4-bit bit reversal. Reverses the order of bits.

## Function

reverse4(a3, a2, a1, a0) = [a0, a1, a2, a3]

| Input | Output |
|-------|--------|
| 0001 | 1000 |
| 1000 | 0001 |
| 0110 | 0110 |
| 1010 | 0101 |

## Architecture

Single layer with 4 neurons, each copying one input bit to its reversed position.

| Output | Copies from | Weights [a3,a2,a1,a0] | Bias |
|--------|-------------|------------------------|------|
| y3 | a0 | [0, 0, 0, 1] | -1 |
| y2 | a1 | [0, 0, 1, 0] | -1 |
| y1 | a2 | [0, 1, 0, 0] | -1 |
| y0 | a3 | [1, 0, 0, 0] | -1 |

## Parameters

| | |
|---|---|
| Inputs | 4 |
| Outputs | 4 |
| Neurons | 4 |
| Layers | 1 |
| Parameters | 8 |
| Magnitude | 8 |

## Usage

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

w = load_file('model.safetensors')

def reverse4(a3, a2, a1, a0):
    inp = torch.tensor([float(a3), float(a2), float(a1), float(a0)])
    return [int((inp @ w[f'y{i}.weight'].T + w[f'y{i}.bias'] >= 0).item())
            for i in [3, 2, 1, 0]]

print(reverse4(1, 0, 0, 0))  # [0, 0, 0, 1]
```

## License

MIT