| import torch |
| from safetensors.torch import load_file |
|
|
| def load_model(path='model.safetensors'): |
| return load_file(path) |
|
|
| def reverse8(a7, a6, a5, a4, a3, a2, a1, a0, weights): |
| """8-bit bit reversal.""" |
| inp = torch.tensor([float(a7), float(a6), float(a5), float(a4), |
| float(a3), float(a2), float(a1), float(a0)]) |
| outputs = [] |
| for i in range(8): |
| y = int((inp @ weights[f'y{i}.weight'].T + weights[f'y{i}.bias'] >= 0).item()) |
| outputs.append(y) |
| return outputs |
|
|
| if __name__ == '__main__': |
| w = load_model() |
| print('reverse8 examples:') |
| test_cases = [ |
| (1, 0, 0, 0, 0, 0, 0, 0), |
| (0, 0, 0, 0, 0, 0, 0, 1), |
| (1, 0, 1, 0, 0, 1, 0, 1), |
| ] |
| for bits in test_cases: |
| result = reverse8(*bits, w) |
| print(f' {list(bits)} -> {result}') |
|
|
