AlexNet相较于LeNet-5具有更深的网络结构,采用relu激活函数。
参数更多,计算量更大,计算速度更慢,精度更高。
net=nn.Sequential(
nn.Conv2d(1,96,kernel_size=11,stride=4,padding=1),nn.ReLU(),
nn.MaxPool2d(kernel_size=3,stride=2),
nn.Conv2d(96,256,kernel_size=5,padding=2),nn.ReLU(),
nn.MaxPool2d(kernel_size=3,stride=2),
nn.Conv2d(256,384,kernel_size=3,padding=1),nn.ReLU(),
nn.Conv2d(384,384,kernel_size=3,padding=1),nn.ReLU(),
nn.Conv2d(384,256,kernel_size=3,padding=1),nn.ReLU(),
nn.MaxPool2d(kernel_size=3,stride=2),
nn.Flatten(),
nn.Linear(6400,4096),nn.ReLU(),
nn.Dropout(p=0.5),
nn.Linear(4096,4096),nn.ReLU(),
nn.Dropout(p=0.5),
nn.Linear(4096,10)
)