| 15 | |
| 16 | |
| 17 | def saveImage(generator,epoch,): |
| 18 | noise = torch.randn(size=(8, config.LATENT_DIM, 1, 1)).to(config.DEVICE) |
| 19 | # fixed labels |
| 20 | y_ = (torch.rand(8, 1) * config.NUM_CLASSES).type(torch.LongTensor) |
| 21 | y_fixed = torch.zeros(8, config.NUM_CLASSES) |
| 22 | y_fixed = y_fixed.scatter_(1, y_.view(8, 1), 1).view(8, config.NUM_CLASSES, 1, 1) |
| 23 | y_fixed = y_fixed.to(config.DEVICE) |
| 24 | |
| 25 | gen_imgs = generator(noise, y_fixed).view(-1, config.CHANNELS, config.IMG_SIZE, config.IMG_SIZE) |
| 26 | |
| 27 | save_image(gen_imgs.data, 'save' + '/%d.png' % (epoch)) |
| 28 | |
| 29 | |
| 30 | def gradient_penalty(critic, real, fake, device): |