| import torch |
| from safetensors.torch import load_file |
|
|
| def load_model(path='model.safetensors'): |
| return load_file(path) |
|
|
| def ctz4(x3, x2, x1, x0, weights): |
| """4-bit count trailing zeros: returns number of trailing 0 bits (0-4).""" |
| inp = torch.tensor([float(x3), float(x2), float(x1), float(x0)]) |
|
|
| |
| p0 = int((inp @ weights['p0.weight'].T + weights['p0.bias'] >= 0).item()) |
| p01 = int((inp @ weights['p01.weight'].T + weights['p01.bias'] >= 0).item()) |
| p012 = int((inp @ weights['p012.weight'].T + weights['p012.bias'] >= 0).item()) |
| all_zero = int((inp @ weights['all_zero.weight'].T + weights['all_zero.bias'] >= 0).item()) |
|
|
| |
| z1 = int((torch.tensor([float(p0), float(x1)]) @ weights['z1.weight'].T + weights['z1.bias'] >= 0).item()) |
| z2 = int((torch.tensor([float(p01), float(x2)]) @ weights['z2.weight'].T + weights['z2.bias'] >= 0).item()) |
| z3 = int((torch.tensor([float(p012), float(x3)]) @ weights['z3.weight'].T + weights['z3.bias'] >= 0).item()) |
|
|
| |
| y2 = int((torch.tensor([float(all_zero)]) @ weights['y2.weight'].T + weights['y2.bias'] >= 0).item()) |
| y1 = int((torch.tensor([float(z2), float(z3)]) @ weights['y1.weight'].T + weights['y1.bias'] >= 0).item()) |
| y0 = int((torch.tensor([float(z1), float(z3)]) @ weights['y0.weight'].T + weights['y0.bias'] >= 0).item()) |
|
|
| return y2, y1, y0 |
|
|
| if __name__ == '__main__': |
| w = load_model() |
| print('CTZ4 examples:') |
| examples = [0b0001, 0b0010, 0b0100, 0b1000, 0b0000, 0b0110, 0b1100] |
| for val in examples: |
| x3, x2, x1, x0 = (val >> 3) & 1, (val >> 2) & 1, (val >> 1) & 1, val & 1 |
| y2, y1, y0 = ctz4(x3, x2, x1, x0, w) |
| count = y2 * 4 + y1 * 2 + y0 |
| print(f' {val:04b} -> {count}') |
|
|
