(loader)
| 166 | |
| 167 | |
| 168 | def test(loader): |
| 169 | cnn.eval() # Change model to 'eval' mode (BN uses moving mean/var). |
| 170 | correct = 0. |
| 171 | total = 0. |
| 172 | for images, labels in loader: |
| 173 | images = images.cuda() |
| 174 | labels = labels.cuda() |
| 175 | |
| 176 | with torch.no_grad(): |
| 177 | pred = cnn(images) |
| 178 | |
| 179 | pred = torch.max(pred.data, 1)[1] |
| 180 | total += labels.size(0) |
| 181 | correct += (pred == labels).sum().item() |
| 182 | |
| 183 | val_acc = correct / total |
| 184 | cnn.train() |
| 185 | return val_acc |
| 186 | |
| 187 | |
| 188 | for epoch in range(args.epochs): |