(model, optimizer, filename="my_checkpoint.pth.tar")
| 30 | |
| 31 | |
| 32 | def save_checkpoint(model, optimizer, filename="my_checkpoint.pth.tar"): |
| 33 | print("=> Saving checkpoint") |
| 34 | checkpoint = { |
| 35 | "state_dict": model.state_dict(), |
| 36 | "optimizer": optimizer.state_dict(), |
| 37 | } |
| 38 | torch.save(checkpoint, filename) |
| 39 | |
| 40 | |
| 41 | def load_checkpoint(checkpoint_file, model, optimizer, lr): |