import torch
from safetensors.torch import load_file

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

def weighted_threshold(x3, x2, x1, x0, weights):
    """Weighted threshold: 4*x3 + 3*x2 + 2*x1 + 1*x0 >= 6."""
    inp = torch.tensor([float(x3), float(x2), float(x1), float(x0)])
    y = int((inp @ weights['y.weight'].T + weights['y.bias'] >= 0).item())
    return y

if __name__ == '__main__':
    w = load_model()
    print('Weighted Threshold (weights: 4,3,2,1, threshold: 6):')
    for i in range(16):
        x3, x2, x1, x0 = (i >> 3) & 1, (i >> 2) & 1, (i >> 1) & 1, i & 1
        y = weighted_threshold(x3, x2, x1, x0, w)
        ws = 4*x3 + 3*x2 + 2*x1 + 1*x0
        print(f'  {x3}{x2}{x1}{x0} (sum={ws:2d}) -> {y}')