import torch
from safetensors.torch import load_file

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

def demux4(d, s1, s0, weights):
    """1:4 Demultiplexer: routes d to output y[s] where s = 2*s1 + s0"""
    inp = torch.tensor([float(d), float(s1), float(s0)])
    outputs = []
    for i in range(4):
        y = int((inp * weights[f'y{i}.weight']).sum() + weights[f'y{i}.bias'] >= 0)
        outputs.append(y)
    return outputs

if __name__ == '__main__':
    w = load_model()
    print('DEMUX4 truth table:')
    print('d  s1 s0 | y0 y1 y2 y3')
    print('---+----+------------')
    for d in [0, 1]:
        for s in range(4):
            s1, s0 = (s >> 1) & 1, s & 1
            result = demux4(d, s1, s0, w)
            print(f'{d}  {s1}  {s0}  |  {result[0]}  {result[1]}  {result[2]}  {result[3]}')