| import torch | |
| from safetensors.torch import load_file | |
| def load_model(path='model.safetensors'): | |
| return load_file(path) | |
| def encode4to2(i3, i2, i1, i0, weights): | |
| """Priority encoder: returns binary index of highest-set input.""" | |
| inp = torch.tensor([float(i3), float(i2), float(i1), float(i0)]) | |
| y1 = int((inp @ weights['y1.weight'].T + weights['y1.bias'] >= 0).item()) | |
| y0 = int((inp @ weights['y0.weight'].T + weights['y0.bias'] >= 0).item()) | |
| return y1, y0 | |
| if __name__ == '__main__': | |
| w = load_model() | |
| print('4-to-2 Priority Encoder:') | |
| for val in range(16): | |
| i3, i2, i1, i0 = (val >> 3) & 1, (val >> 2) & 1, (val >> 1) & 1, val & 1 | |
| y1, y0 = encode4to2(i3, i2, i1, i0, w) | |
| print(f' {i3}{i2}{i1}{i0} -> {y1}{y0} (={2*y1+y0})') | |