:param gen: 生成模型 :param val_loader:加载的验证集数据集 :param epoch: 迭代次数 :param folder: 保存文件路径 :return:
(gen, val_loader, epoch, folder)
| 9 | from torchvision.utils import save_image |
| 10 | |
| 11 | def save_some_examples(gen, val_loader, epoch, folder): |
| 12 | """ |
| 13 | :param gen: 生成模型 |
| 14 | :param val_loader:加载的验证集数据集 |
| 15 | :param epoch: 迭代次数 |
| 16 | :param folder: 保存文件路径 |
| 17 | :return: |
| 18 | """ |
| 19 | x, y = next(iter(val_loader)) |
| 20 | x, y = x.to(config.DEVICE), y.to(config.DEVICE) |
| 21 | gen.eval() |
| 22 | with torch.no_grad(): |
| 23 | y_fake = gen(x) |
| 24 | y_fake = y_fake * 0.5 + 0.5 # remove normalization# |
| 25 | save_image(y_fake, folder + f"/y_gen_{epoch}.png") |
| 26 | save_image(x * 0.5 + 0.5, folder + f"/input_{epoch}.png") |
| 27 | if epoch == 1: |
| 28 | save_image(y * 0.5 + 0.5, folder + f"/label_{epoch}.png") |
| 29 | gen.train() |
| 30 | |
| 31 | |
| 32 | def save_checkpoint(model, optimizer, filename="my_checkpoint.pth.tar"): |