Method __init__

StyleGAN/net/model.py:29–42

(self,in_channels,out_channels,kernel_size = 3,stride = 1,
                 padding = 1,gain = 2)

#紧跟PixelNorm之后的3 x 3卷积
class WSConv2d(torch.nn.Module):
    def __init__(self,in_channels,out_channels,kernel_size = 3,stride = 1,
                 padding = 1,gain = 2):
        super(WSConv2d, self).__init__()
        self.conv = torch.nn.Conv2d(in_channels,out_channels,kernel_size,stride,padding)
        self.scale = (gain / (in_channels * (kernel_size**2)))**0.5
        self.bias = self.conv.bias
        self.conv.bias = None

        #initialize conv layer
        #torch.init.normal_：给tensor初始化，一般是给网络中参数weight初始化，初始化参数值符合正态分布。
        #torch.init.normal_(tensor,mean=,std=) ,mean:均值，std:正态分布的标准差
        torch.nn.init.normal_(self.conv.weight)
        #将其偏置设置为0
        torch.nn.init.zeros_(self.bias)

    def forward(self,x):
        out = self.conv(x * self.scale) + self.bias.view(1,self.bias.shape[0],1,1)