我就废话不多说了，直接上代码吧！
class Net(nn.Module): def __init__(self , model): super(Net, self).__init__() #取掉model的后两层 self.resnet_layer = nn.Sequential(*list(model.children())[:-2]) self.transion_layer = nn.ConvTranspose2d(2048, 2048, kernel_size=14, stride=3) self.pool_layer = nn.MaxPool2d(32) self.Linear_layer = nn.Linear(2048, 8) def forward(self, x): x = self.resnet_layer(x) x = self.transion_layer(x) x = self.pool_layer(x) x = x.view(x.size(0), -1) x = self.Linear_layer(x) return x
resnet = models.resnet50(pretrained=True) model = Net(resnet)
以上这篇pytorch 修改预训练model实例就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持。