pytorch深度学习：卷积神经网络

CNN中的果蝇，哈哈。

import torch
from torchvision import datasets,transforms
from torch import nn,optim
import torch.nn.functional as F

trans=(transforms.ToTensor(),transforms.Normalize((0.1307,),(0.3081,)))
trainset=datasets.MNIST('data',train=True,download=True,transform=trans)
testset=datasets.MNIST('data',train=False,download=True,transform=trans)

class LeNet(nn.Module):
    def __init__(self):
        super(LeNet, self).__init__()
        self.c1=nn.Conv2d(1,6,(5,5))
        self.c3=nn.Conv2d(6,16,5)
        self.fc1=nn.Linear(16*4*4,120)
        self.fc2=nn.Linear(120,84)
        self.fc3=nn.Linear(84,10)

    def forward(self,x):
        x=F.max_pool2d(F.relu(self.c1(x)),2)
        x=F.max_pool2d(F.relu(self.c3(x)),2)
        x=x.view(-1,self.num_flat_features(x))
        x=F.relu(self.fc1(x))
        x=F.relu(self.fc2(x))
        x=self.fc3(x)
        return x

    def sum_flat_features(self,x):
        size=x.size()[1:]
        num_features=1
        for s in size:
            num_features*=s
        return num_features