(train_x, val_x)
| 60 | |
| 61 | |
| 62 | def normalize(train_x, val_x): |
| 63 | mean = [0.4914, 0.4822, 0.4465] |
| 64 | std = [0.2023, 0.1994, 0.2010] |
| 65 | train_x /= 255 |
| 66 | val_x /= 255 |
| 67 | for ch in range(0, 2): |
| 68 | train_x[:, ch, :, :] -= mean[ch] |
| 69 | train_x[:, ch, :, :] /= std[ch] |
| 70 | val_x[:, ch, :, :] -= mean[ch] |
| 71 | val_x[:, ch, :, :] /= std[ch] |
| 72 | return train_x, val_x |
| 73 | |
| 74 | |
| 75 | def load(): |