我就廢話不多說了，直接上代碼吧！
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class Net(nn.Module): def __init__(self , model): super(Net, self).__init__() #取掉model的后兩層 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 |
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resnet = models.resnet50(pretrained=True)model = Net(resnet) |
以上這篇pytorch 修改預訓練model實例就是小編分享給大家的全部內(nèi)容了，希望能給大家一個參考，也希望大家多多支持服務器之家。
原文鏈接：https://blog.csdn.net/whut_ldz/article/details/78874977
