pytorch 修改预训练model实例

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。