import torch
from safetensors.torch import load_file

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

def isone4(a3, a2, a1, a0, weights):
    """Returns 1 if 4-bit input equals 1 (0001), else 0"""
    inp = torch.tensor([float(a3), float(a2), float(a1), float(a0)])
    return int((inp @ weights['neuron.weight'].T + weights['neuron.bias'] >= 0).item())

if __name__ == '__main__':
    w = load_model()
    print('isone4 truth table:')
    for i in range(16):
        a3, a2, a1, a0 = (i >> 3) & 1, (i >> 2) & 1, (i >> 1) & 1, i & 1
        result = isone4(a3, a2, a1, a0, w)
        marker = ' <-- ONE' if result else ''
        print(f'  {a3}{a2}{a1}{a0} (={i:2d}) -> {result}{marker}')