| import torch | |
| from safetensors.torch import load_file | |
| def load_model(path='model.safetensors'): | |
| return load_file(path) | |
| def atmost4of5(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('atmost4outof5 selected outputs:') | |
| for s in range(6): | |
| bits = [(1 if j < s else 0) for j in range(5)] | |
| print(f' sum={s}: {bits} -> {atmost4of5(*bits, w)}') | |