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服务器之家。

原文链接：https://blog.csdn.net/whut_ldz/article/details/78874977