Method __init__

SRGAN/models.py:34–39

(self,in_channels,scale_factor)

#采用PixelShuffle进行上采样
class UpsampleBlock(torch.nn.Module):
    def __init__(self,in_channels,scale_factor):
        super(UpsampleBlock, self).__init__()
        self.conv = torch.nn.Conv2d(in_channels,in_channels*scale_factor**2,kernel_size = (3,3),stride = (1,1),padding=(1,1))
        #(in_channels * 4,H,W) => (in_channels,H*2,W*2)
        self.ps = torch.nn.PixelShuffle(scale_factor)
        self.act = torch.nn.PReLU(num_parameters=in_channels)
    def forward(self,x):
        out = self.act(self.ps(self.conv(x)))
        return  out