Class Decoder

evaluation/net.py:117–156

            return  adain_feat

class Decoder(nn.Module):
    def __init__(self, gpu_ids=[]):
        super(Decoder, self).__init__()
        decoder = [
            nn.ReflectionPad2d((1, 1, 1, 1)),
            nn.Conv2d(512, 256, (3, 3)),
            nn.ReLU(), # 256
            nn.Upsample(scale_factor=2, mode='nearest'),
            nn.ReflectionPad2d((1, 1, 1, 1)),
            nn.Conv2d(256, 256, (3, 3)),
            nn.ReLU(),
            nn.ReflectionPad2d((1, 1, 1, 1)),
            nn.Conv2d(256, 256, (3, 3)),
            nn.ReLU(),
            nn.ReflectionPad2d((1, 1, 1, 1)),
            nn.Conv2d(256, 256, (3, 3)),
            nn.ReLU(),
            nn.ReflectionPad2d((1, 1, 1, 1)),
            nn.Conv2d(256, 128, (3, 3)),
            nn.ReLU(),# 128
            nn.Upsample(scale_factor=2, mode='nearest'),
            nn.ReflectionPad2d((1, 1, 1, 1)),
            nn.Conv2d(128, 128, (3, 3)),
            nn.ReLU(),
            nn.ReflectionPad2d((1, 1, 1, 1)),
            nn.Conv2d(128, 64, (3, 3)),
            nn.ReLU(),# 64
            nn.Upsample(scale_factor=2, mode='nearest'),
            nn.ReflectionPad2d((1, 1, 1, 1)),
            nn.Conv2d(64, 64, (3, 3)),
            nn.ReLU(),
            nn.ReflectionPad2d((1, 1, 1, 1)),
            nn.Conv2d(64, 3, (3, 3))
            ]
        self.decoder = nn.Sequential(*decoder)

    def forward(self, adain_feat):
        fake_image = self.decoder(adain_feat)

        return fake_image