import torch.nn as nn


# 定义VGG16的网络结构
class VGGNet(nn.Module):
    def __init__(self, num_classes=10):
        super(VGGNet, self).__init__()
        self.features = self._make_layers()
        self.classifier = nn.Sequential(
            nn.Linear(512 * 1 * 1, 512),
            nn.ReLU(inplace=True),
            nn.Dropout(),
            nn.Linear(512, 512),
            nn.ReLU(inplace=True),
            nn.Dropout(),
            nn.Linear(512, num_classes)
        )

    def _make_layers(self):
        layers = []
        in_channels = 3
        cfg = [64, 64, 'M', 128, 128, 'M', 256, 256, 256, 'M', 512, 512, 512, 'M', 512, 512, 512, 'M']
        for v in cfg:
            if v == 'M':
                layers += [nn.MaxPool2d(kernel_size=2, stride=2)]
            else:
                conv2d = nn.Conv2d(in_channels, v, kernel_size=3, padding=1)
                layers += [conv2d, nn.ReLU(inplace=True)]
                in_channels = v
        return nn.Sequential(*layers)

    def forward(self, x):
        x = self.features(x)
        x = x.view(x.size(0), -1)
        x = self.classifier(x)
        return x