| import torch | |
| from device import device | |
| model = torch.load("model.pth", weights_only=False).to(device) | |
| def run(test): | |
| with torch.no_grad(): | |
| test_data = torch.tensor([test], dtype=torch.float).to(device) | |
| predictions: torch.Tensor = model(test_data) | |
| return predictions.squeeze().item() | |
| if __name__ == '__main__': | |
| x, y = map(int, input().split()) | |
| print(run([x, y])) | |