(model, dataloader)
| 108 | |
| 109 | |
| 110 | def evaluate(model, dataloader): |
| 111 | model.eval() |
| 112 | correct = 0 |
| 113 | total = 0 |
| 114 | for data in dataloader: |
| 115 | inputs, labels = data[0], data[1]['Young'] |
| 116 | inputs, labels = inputs.to(args.device), labels.to(args.device) |
| 117 | outputs = model(inputs) |
| 118 | _, predicted = outputs.max(1) |
| 119 | total += labels.size(0) |
| 120 | correct += predicted.eq(labels).sum().item() |
| 121 | model.train() |
| 122 | return correct / total |
| 123 | |
| 124 | |
| 125 | if __name__ == "__main__": |
no test coverage detected