model.py

import torch
from safetensors.torch import load_file

def load_model(path='model.safetensors'):
    return load_file(path)

def encode4to2(i3, i2, i1, i0, weights):
    """Priority encoder: returns binary index of highest-set input."""
    inp = torch.tensor([float(i3), float(i2), float(i1), float(i0)])
    y1 = int((inp @ weights['y1.weight'].T + weights['y1.bias'] >= 0).item())
    y0 = int((inp @ weights['y0.weight'].T + weights['y0.bias'] >= 0).item())
    return y1, y0

if __name__ == '__main__':
    w = load_model()
    print('4-to-2 Priority Encoder:')
    for val in range(16):
        i3, i2, i1, i0 = (val >> 3) & 1, (val >> 2) & 1, (val >> 1) & 1, val & 1
        y1, y0 = encode4to2(i3, i2, i1, i0, w)
        print(f'  {i3}{i2}{i1}{i0} -> {y1}{y0} (={2*y1+y0})')