| import torch | |
| from safetensors.torch import load_file | |
| def load_model(path='model.safetensors'): | |
| return load_file(path) | |
| def weighted_threshold(x3, x2, x1, x0, weights): | |
| """Weighted threshold: 4*x3 + 3*x2 + 2*x1 + 1*x0 >= 6.""" | |
| inp = torch.tensor([float(x3), float(x2), float(x1), float(x0)]) | |
| y = int((inp @ weights['y.weight'].T + weights['y.bias'] >= 0).item()) | |
| return y | |
| if __name__ == '__main__': | |
| w = load_model() | |
| print('Weighted Threshold (weights: 4,3,2,1, threshold: 6):') | |
| for i in range(16): | |
| x3, x2, x1, x0 = (i >> 3) & 1, (i >> 2) & 1, (i >> 1) & 1, i & 1 | |
| y = weighted_threshold(x3, x2, x1, x0, w) | |
| ws = 4*x3 + 3*x2 + 2*x1 + 1*x0 | |
| print(f' {x3}{x2}{x1}{x0} (sum={ws:2d}) -> {y}') | |