| import torch | |
| from safetensors.torch import load_file | |
| def load_model(path='model.safetensors'): | |
| return load_file(path) | |
| def minority5(a, b, c, d, e, weights): | |
| inp = torch.tensor([float(a), float(b), float(c), float(d), float(e)]) | |
| return int((inp @ weights['neuron.weight'].T + weights['neuron.bias'] >= 0).item()) | |
| if __name__ == '__main__': | |
| w = load_model() | |
| print('minority5 sample outputs:') | |
| print(f' 00000 -> {minority5(0,0,0,0,0,w)}') | |
| print(f' 00011 -> {minority5(0,0,0,1,1,w)}') | |
| print(f' 00111 -> {minority5(0,0,1,1,1,w)}') | |