| import torch | |
| from safetensors.torch import load_file | |
| def load_model(path='model.safetensors'): | |
| return load_file(path) | |
| def onehot_encode(a1, a0, weights): | |
| """Convert 2-bit binary to 4-bit one-hot encoding.""" | |
| inp = torch.tensor([float(a1), float(a0)]) | |
| y0 = int((inp @ weights['y0.weight'].T + weights['y0.bias'] >= 0).item()) | |
| y1 = int((inp @ weights['y1.weight'].T + weights['y1.bias'] >= 0).item()) | |
| y2 = int((inp @ weights['y2.weight'].T + weights['y2.bias'] >= 0).item()) | |
| y3 = int((inp @ weights['y3.weight'].T + weights['y3.bias'] >= 0).item()) | |
| return y3, y2, y1, y0 | |
| if __name__ == '__main__': | |
| w = load_model() | |
| print('One-Hot Encoder (2-to-4):') | |
| for val in range(4): | |
| a1, a0 = (val >> 1) & 1, val & 1 | |
| y3, y2, y1, y0 = onehot_encode(a1, a0, w) | |
| print(f' {val} ({a1}{a0}) -> {y3}{y2}{y1}{y0}') | |