李沐动手深度学习10：多层感知机

import torch
from torch import nn
from d2l import torch as d2l

# 隐藏层包含256个隐藏单元，并使用了ReLU激活函数
net = nn.Sequential(nn.Flatten(),nn.Linear(784,256),nn.ReLU(),nn.Linear(256,10))

def init_weights(m):
    if type(m) == nn.Linear:
        nn.init.normal_(m.weight,std=0,)
        
net.apply(init_weights)

# 训练过程
batch_size, lr, num_epochs = 256, 0.1, 10
loss = nn.CrossEntropyLoss()
trainer = torch.optim.SGD(net.parameters(), lr=lr)

train_iter, test_iter = d2l.load_data_fashion_mnist(batch_size)
d2l.train_ch3(net, train_iter, test_iter, loss, num_epochs, trainer)