pytorch 固定部分参数训练的方法

optimizer.SGD(filter(lambda p: p.requires_grad, model.parameters()), lr=1e-3)

j = Variable(torch.randn(5,5), requires_grad=True)

m = nn.Linear(10,10)

for i in m.parameters():  i.requires_grad=False

for p in self.parameters():  p.requires_grad=False

class Net(nn.Module):  def __init__(self):    super(Net, self).__init__()    self.conv1 = nn.Conv2d(1, 6, 5)    self.conv2 = nn.Conv2d(6, 16, 5)    for p in self.parameters():      p.requires_grad=False    self.fc1 = nn.Linear(16 * 5 * 5, 120)    self.fc2 = nn.Linear(120, 84)    self.fc3 = nn.Linear(84, 10)