Method __init__

networks/sr_arch_singlec.py:9–87

(self, in_channel=3, dim_channel=256)

class SRNet(nn.Module):
    def __init__(self, in_channel=3, dim_channel=256):
        super().__init__()
        self.conv_first_32 = nn.Sequential(
            SpectralNorm(nn.Conv2d(in_channel, dim_channel//4, 3, 1, 1)),
            nn.LeakyReLU(0.2),
        )
        self.conv_first_16 = nn.Sequential(
            SpectralNorm(nn.Conv2d(dim_channel//4, dim_channel//2, 3, 2, 1)),
            nn.LeakyReLU(0.2),
        )
        self.conv_first_8 = nn.Sequential(
            SpectralNorm(nn.Conv2d(dim_channel//2, dim_channel, 3, 2, 1)),
            nn.LeakyReLU(0.2),
            SpectralNorm(nn.Conv2d(dim_channel, dim_channel, 3, 1, 1)),
        )
        self.conv_body_16 = nn.Sequential(
            SpectralNorm(nn.Conv2d(dim_channel+dim_channel//2, dim_channel, 3, 1, 1)),
            nn.LeakyReLU(0.2),
            SpectralNorm(nn.Conv2d(dim_channel, dim_channel, 3, 1, 1)),
        )
        self.conv_body_32 = nn.Sequential(
            SpectralNorm(nn.Conv2d(dim_channel+dim_channel//4, dim_channel, 3, 1, 1)),
            nn.LeakyReLU(0.2),
            SpectralNorm(nn.Conv2d(dim_channel, dim_channel, 3, 1, 1)),
        )

        self.conv_up = nn.Sequential(
            nn.Upsample(scale_factor=2, mode='bilinear'), #64*64*256
            SpectralNorm(nn.Conv2d(dim_channel, dim_channel, 3, 1, 1)),
            nn.LeakyReLU(0.2),
            ResTextBlockV2(dim_channel, dim_channel),
            SpectralNorm(nn.Conv2d(dim_channel, dim_channel, 3, 1, 1)),
        )

        self.conv_final = nn.Sequential(
            SpectralNorm(nn.Conv2d(dim_channel, dim_channel//2, 3, 1, 1)),
            nn.LeakyReLU(0.2),
            nn.Upsample(scale_factor=2, mode='bilinear'), #128*128*256
            SpectralNorm(nn.Conv2d(dim_channel//2, dim_channel//4, 3, 1, 1)),
            nn.LeakyReLU(0.2),
            ResTextBlockV2(dim_channel//4, dim_channel//4),
            SpectralNorm(nn.Conv2d(dim_channel//4, 3, 3, 1, 1)),
            nn.Tanh()
        )


        self.conv_32_scale = nn.Sequential(
            SpectralNorm(nn.Conv2d(dim_channel, dim_channel, 3, 1, 1)),
            nn.LeakyReLU(0.2),
            SpectralNorm(nn.Conv2d(dim_channel, dim_channel, 3, 1, 1)),
        )
        self.conv_32_shift = nn.Sequential(
            SpectralNorm(nn.Conv2d(dim_channel, dim_channel, 3, 1, 1)),
            nn.LeakyReLU(0.2),
            SpectralNorm(nn.Conv2d(dim_channel, dim_channel, 3, 1, 1)),
        )
        self.conv_32_fuse = nn.Sequential(
            ResTextBlockV2(2*dim_channel, dim_channel)