import torch
from safetensors.torch import load_file

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

def atmost2of5(a, b, c, d, e, weights):
    inp = torch.tensor([float(a), float(b), float(c), float(d), float(e)])
    return int((inp @ weights['neuron.weight'].T + weights['neuron.bias'] >= 0).item())

if __name__ == '__main__':
    w = load_model()
    print('atmost2outof5 selected outputs:')
    for s in [0, 1, 2, 3, 4, 5]:
        bits = [(1 if j < s else 0) for j in range(5)]
        print(f'  sum={s}: {bits} -> {atmost2of5(*bits, w)}')