pytorch基础（4）-----搭建模型网络的两种方法

方法一：采用torch.nn.Module模块

import torch
import torch.nn.functional as F
 
#法1
class Net(torch.nn.Module):
    def __init__(self,n_feature,n_hidden,n_output):
        super(Net,self).__init__()
        self.hidden = torch.nn.Linear(n_feature,n_hidden)
        self.predict = torch.nn.Linear(n_hidden,n_output)
    def forward(self,x):
        x = F.relu(self.hidden(x))
        out = self.predict(x)
        return x
net1 = Net(2,10,2)
print(net1)

打印的结果：

Net(
  (hidden): Linear(in_features=2, out_features=10, bias=True)
  (predict): Linear(in_features=10, out_features=2, bias=True)
)

方法二：类似keras的sequencial搭建网络的方法

net2 = torch.nn.Sequential(
    torch.nn.Linear(2,10),
    torch.nn.ReLU(),
    torch.nn.Linear(10,2),
)
print(net2)

打印结果：

Sequential(
  (0): Linear(in_features=2, out_features=10, bias=True)
  (1): ReLU()
  (2): Linear(in_features=10, out_features=2, bias=True)
)