fcn.py 文件源码

def _initialize_weights(self):
        vgg16 = torchvision.models.vgg16(pretrained=True)

        for m in self.modules():
            if isinstance(m, nn.ConvTranspose2d):
                assert m.kernel_size[0] == m.kernel_size[1]
                m.weight.data = weight_init.kaiming_normal(m.weight.data)
        for a, b in zip(vgg16.features, self.features):
            if (isinstance(a, nn.Conv2d) and isinstance(b, nn.Conv2d)):
                b.weight.data = a.weight.data
                b.bias.data = a.bias.data
        for i in [0, 3]:
            a, b = vgg16.classifier[i], self.classifier[i]
            b.weight.data = a.weight.data.view(b.weight.size())
            b.bias.data = a.bias.data.view(b.bias.size())