(model, data_loader, device)
| 144 | |
| 145 | @torch.no_grad() |
| 146 | def evaluate(model, data_loader, device): |
| 147 | model.eval() |
| 148 | |
| 149 | # 验证样本总个数 |
| 150 | total_num = len(data_loader.dataset) |
| 151 | |
| 152 | # 用于存储预测正确的样本个数 |
| 153 | sum_num = torch.zeros(1).to(device) |
| 154 | |
| 155 | data_loader = tqdm(data_loader, file=sys.stdout) |
| 156 | |
| 157 | for step, data in enumerate(data_loader): |
| 158 | images, labels = data |
| 159 | pred = model(images.to(device)) |
| 160 | pred = torch.max(pred, dim=1)[1] |
| 161 | sum_num += torch.eq(pred, labels.to(device)).sum() |
| 162 | |
| 163 | return sum_num.item() / total_num |
| 164 | |
| 165 |