64x64 Architecture

architectures.py

# 64x64
class Generator64(nn.Module):
    def __init__(self, ngpu):
        super(Generator64, self).__init__()
        self.ngpu = ngpu
        self.main = nn.Sequential(
            nn.ConvTranspose2d(100, 512, kernel_size=4, stride=1, padding=0),
            nn.BatchNorm2d(512),
            nn.LeakyReLU(0.2),
            nn.ConvTranspose2d(512, 256, kernel_size=4, stride=2, padding=1),
            nn.BatchNorm2d(256),
            nn.LeakyReLU(0.2),
            nn.ConvTranspose2d(256, 128, kernel_size=4, stride=2, padding=1),
            nn.BatchNorm2d(128),
            nn.LeakyReLU(0.2),
            nn.ConvTranspose2d(128, 64, kernel_size=4, stride=2, padding=1),
            nn.BatchNorm2d(64),
            nn.ConvTranspose2d(64, 1, kernel_size=4, stride=2, padding=1),
        )

    def forward(self, input):
        return self.main(input)


class Discriminator64(nn.Module):
    def __init__(self, ngpu):
        super(Discriminator64, self).__init__()
        self.ngpu = ngpu
        self.main = nn.Sequential(
            nn.Conv2d(1, 64, kernel_size=4, stride=2, padding=1),
            nn.LeakyReLU(0.2),
            nn.Dropout(0.1),
            nn.Conv2d(64, 128, kernel_size=4, stride=2, padding=1),
            nn.BatchNorm2d(128),
            nn.LeakyReLU(0.2),
            nn.Dropout(0.1),
            nn.Conv2d(128, 256, kernel_size=4, stride=2, padding=1),
            nn.BatchNorm2d(256),
            nn.LeakyReLU(0.2),
            nn.Dropout(0.1),
            nn.Conv2d(256, 512, kernel_size=4, stride=2, padding=1),
            nn.BatchNorm2d(512),
            nn.LeakyReLU(0.2),
            nn.Dropout(0.1),
            nn.Conv2d(512, 1, kernel_size=4, stride=1, padding=0),
            nn.Sigmoid()
        )

    def forward(self, input):
        return self.main(input)