| import torch | |
| from safetensors.torch import load_file | |
| def load_model(path='model.safetensors'): | |
| return load_file(path) | |
| def isone8(a7, a6, a5, a4, a3, a2, a1, a0, weights): | |
| """Returns 1 if 8-bit input equals 1 (00000001), else 0""" | |
| inp = torch.tensor([float(a7), float(a6), float(a5), float(a4), | |
| float(a3), float(a2), float(a1), float(a0)]) | |
| return int((inp @ weights['neuron.weight'].T + weights['neuron.bias'] >= 0).item()) | |
| if __name__ == '__main__': | |
| w = load_model() | |
| print('isone8 selected tests:') | |
| for i in [0, 1, 2, 127, 128, 255]: | |
| bits = [(i >> (7-j)) & 1 for j in range(8)] | |
| result = isone8(*bits, w) | |
| marker = ' <-- ONE' if result else '' | |
| print(f' {i:3d} ({i:08b}) -> {result}{marker}') | |