pytorch 6 build_nn_quickly 快速搭建神经网络

import torch
import torch.nn.functional as F


# replace following class code with an easy sequential network
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)   # hidden layer
        self.predict = torch.nn.Linear(n_hidden, n_output)   # output layer

    def forward(self, x):
        x = F.relu(self.hidden(x))      # activation function for hidden layer
        x = self.predict(x)             # linear output
        return x

net1 = Net(1, 10, 1)

print(net1)     # net1 architecture

> Net(
>   (hidden): Linear(in_features=1, out_features=10, bias=True)
>   (predict): Linear(in_features=10, out_features=1, bias=True)
> )

easy and fast way to build your network

• 两种方法使用效果完全相同

# easy and fast way to build your network
net2 = torch.nn.Sequential(
    torch.nn.Linear(1, 10),
    torch.nn.ReLU(),
    torch.nn.Linear(10, 1)
)

print(net2)     # net2 architecture

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

END