Pytorch实现AlexNet

示例代码：

import torch.nn as nn


class AlexNet(nn.Module):
    def __init__(self):
        super(AlexNet, self).__init__()
        self.conv1 = nn.Sequential(
            nn.Conv2d(in_channels=3,
                      out_channels=96,
                      kernel_size=2,
                      stride=1,
                      padding=1),
            nn.ReLU(),
            nn.MaxPool2d(kernel_size=2)
        )
        self.conv2 = nn.Sequential(
            nn.Conv2d(in_channels=96,
                      out_channels=256,
                      kernel_size=2,
                      stride=1,
                      padding=1),
            nn.ReLU(),
            nn.MaxPool2d(kernel_size=2)
        )

        self.conv3 = nn.Sequential(
            nn.Conv2d(in_channels=256,
                      out_channels=384,
                      kernel_size=3,
                      stride=1,
                      padding=1),
            nn.ReLU(),
        )
        self.conv4 = nn.Sequential(
            nn.Conv2d(in_channels=384,
                      out_channels=384,
                      kernel_size=3,
                      stride=1,
                      padding=1),
            nn.ReLU(),
        )
        self.conv5 = nn.Sequential(
            nn.Conv2d(in_channels=384,
                      out_channels=256,
                      kernel_size=2,
                      stride=1,
                      padding=1),
            nn.ReLU(),
            nn.MaxPool2d(kernel_size=2)
        )

        self.fc1 = nn.Sequential(
            nn.Linear(4 * 4 * 256, 4096),
            nn.ReLU(),
            nn.Dropout(p=0.8)
        )

        self.fc2 = nn.Sequential(
            nn.Linear(4096, 1024),
            nn.ReLU(),
            nn.Dropout(p=0.8)
        )

        self.out = nn.Linear(1024, 10)

    def forward(self, inputs):
        network = self.conv1(inputs)
        network = self.conv2(network)
        network = self.conv3(network)
        network = self.conv4(network)
        network = self.conv5(network)
        network = network.view(network.size(0), -1)
        network = self.fc1(network)
        network = self.fc2(network)
        out = self.out(network)
        return out, network

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