|
|
---
|
|
|
license: mit
|
|
|
tags:
|
|
|
- pytorch
|
|
|
- safetensors
|
|
|
- threshold-logic
|
|
|
- neuromorphic
|
|
|
---
|
|
|
|
|
|
# threshold-min2
|
|
|
|
|
|
Minimum of two 2-bit unsigned integers.
|
|
|
|
|
|
## Function
|
|
|
|
|
|
min2(a, b) = min(a, b) where a, b are 2-bit unsigned integers (0-3)
|
|
|
|
|
|
Inputs: a1, a0, b1, b0 (MSB first)
|
|
|
Outputs: m1, m0 = binary representation of min(a, b)
|
|
|
|
|
|
## Truth Table
|
|
|
|
|
|
| a | b | min |
|
|
|
|---|---|-----|
|
|
|
| 0 | 0 | 0 |
|
|
|
| 0 | 1 | 0 |
|
|
|
| 0 | 2 | 0 |
|
|
|
| 0 | 3 | 0 |
|
|
|
| 1 | 0 | 0 |
|
|
|
| 1 | 1 | 1 |
|
|
|
| 1 | 2 | 1 |
|
|
|
| 1 | 3 | 1 |
|
|
|
| 2 | 0 | 0 |
|
|
|
| 2 | 1 | 1 |
|
|
|
| 2 | 2 | 2 |
|
|
|
| 2 | 3 | 2 |
|
|
|
| 3 | 0 | 0 |
|
|
|
| 3 | 1 | 1 |
|
|
|
| 3 | 2 | 2 |
|
|
|
| 3 | 3 | 3 |
|
|
|
|
|
|
## Architecture
|
|
|
|
|
|
7-layer circuit:
|
|
|
1. Layer 1: Bit comparisons and passthrough (10 neurons)
|
|
|
2. Layer 2: Equality detection (9 neurons)
|
|
|
3. Layer 3: Partial comparison (8 neurons)
|
|
|
4. Layer 4: Full a > b and a == b (6 neurons)
|
|
|
5. Layer 5: a <= b computation (5 neurons)
|
|
|
6. Layer 6: MUX selection (4 neurons)
|
|
|
7. Layer 7: Final OR (2 neurons)
|
|
|
|
|
|
## Parameters
|
|
|
|
|
|
| | |
|
|
|
|---|---|
|
|
|
| Inputs | 4 |
|
|
|
| Outputs | 2 |
|
|
|
| Neurons | 44 |
|
|
|
| Layers | 7 |
|
|
|
| Parameters | 186 |
|
|
|
| Magnitude | 95 |
|
|
|
|
|
|
## Usage
|
|
|
|
|
|
```python
|
|
|
from safetensors.torch import load_file
|
|
|
import torch
|
|
|
|
|
|
w = load_file('model.safetensors')
|
|
|
|
|
|
# Use model.py for full implementation
|
|
|
from model import min2, load_model
|
|
|
w = load_model()
|
|
|
m1, m0 = min2(1, 0, 0, 1, w) # min(2, 1) = 1
|
|
|
print(2*m1 + m0) # 1
|
|
|
```
|
|
|
|
|
|
## License
|
|
|
|
|
|
MIT
|
|
|
|
