61228f3243eaee39cba31a9abd2afc6ead9612a8,implementations/ccgan/ccgan.py,,,#,51

Before Change

discriminator.apply(weights_init_normal)

// Configure data loader
os.makedirs("../../data/cifar10", exist_ok=True)
cifar_loader = torch.utils.data.DataLoader(
    datasets.CIFAR10("../../data/cifar10", train=True, download=True,
                   transform=transforms.Compose([
                       transforms.Resize(opt.img_size),

After Change

transforms_ = [ transforms.Resize((opt.img_size, opt.img_size), Image.BICUBIC),
                transforms.ToTensor(),
                transforms.Normalize((0.5,0.5,0.5), (0.5,0.5,0.5)) ]
transforms_lr = [ transforms.Resize((opt.img_size//4, opt.img_size//4), Image.BICUBIC),
                transforms.ToTensor(),
                transforms.Normalize((0.5,0.5,0.5), (0.5,0.5,0.5)) ]
dataloader = DataLoader(ImageDataset("../../data/%s" % opt.dataset_name,
                        transforms_x=transforms_, transforms_lr=transforms_lr),
                        batch_size=opt.batch_size, shuffle=True, num_workers=opt.n_cpu)

// Optimizers
optimizer_G = torch.optim.Adam(generator.parameters(), lr=opt.lr, betas=(opt.b1, opt.b2))
optimizer_D = torch.optim.Adam(discriminator.parameters(), lr=opt.lr, betas=(opt.b1, opt.b2))

Instances