| import torch | |
| from safetensors.torch import load_file | |
| def load_model(path='model.safetensors'): | |
| return load_file(path) | |
| def mux8(d0, d1, d2, d3, d4, d5, d6, d7, s2, s1, s0, weights): | |
| """8:1 Multiplexer: returns d[s] where s = 4*s2 + 2*s1 + s0""" | |
| inp = torch.tensor([float(d0), float(d1), float(d2), float(d3), | |
| float(d4), float(d5), float(d6), float(d7), | |
| float(s2), float(s1), float(s0)]) | |
| l1 = (inp @ weights['layer1.weight'].T + weights['layer1.bias'] >= 0).float() | |
| out = (l1 @ weights['layer2.weight'].T + weights['layer2.bias'] >= 0).float() | |
| return int(out.item()) | |
| if __name__ == '__main__': | |
| w = load_model() | |
| print('MUX8 verification:') | |
| for s in range(8): | |
| s2, s1, s0 = (s >> 2) & 1, (s >> 1) & 1, s & 1 | |
| d = [0] * 8 | |
| d[s] = 1 | |
| result = mux8(*d, s2, s1, s0, w) | |
| print(f' s={s} ({s2}{s1}{s0}), d[{s}]=1 -> {result}') | |