| import torch | |
| from safetensors.torch import load_file | |
| def load_model(path='model.safetensors'): | |
| return load_file(path) | |
| def atmost2of3(a, b, c, weights): | |
| """Returns 1 if at most 2 of 3 inputs are high (NAND)""" | |
| inp = torch.tensor([float(a), float(b), float(c)]) | |
| return int((inp @ weights['neuron.weight'].T + weights['neuron.bias'] >= 0).item()) | |
| if __name__ == '__main__': | |
| w = load_model() | |
| print('atmost2outof3 (NAND3) truth table:') | |
| for i in range(8): | |
| a, b, c = (i >> 2) & 1, (i >> 1) & 1, i & 1 | |
| print(f' {a}{b}{c} -> {atmost2of3(a, b, c, w)}') | |