动手学习pytorch——（3）多层感知机

import torch
from torch import nn
from torch.nn import init
import numpy as np
import sys
sys.path.append("/home/kesci/input")
import d2lzh1981 as d2l

num_inputs, num_outputs, num_hiddens = 784, 10, 256
    
net = nn.Sequential(
        d2l.FlattenLayer(),
        nn.Linear(num_inputs, num_hiddens),
        nn.ReLU(),
        nn.Linear(num_hiddens, num_outputs), 
        )
    
for params in net.parameters(): 
    init.normal_(params, mean=0, std=0.01)   #参数初始化

batch_size = 256
num_epochs = 5
train_iter, test_iter = d2l.load_data_fashion_mnist(batch_size,root=‘/home/kesci/input/FashionMNIST2065‘)

loss = torch.nn.CrossEntropyLoss()
optimizer = torch.optim.SGD(net.parameters(), lr=0.5)

d2l.train_ch3(net, train_iter, test_iter, loss, num_epo