pytorch残差网络代码

以下是一份简单的 Inception v3 网络的 PyTorch 代码：

import torch.nn as nn
import torch.nn.functional as F

class InceptionV3(nn.Module):
    def __init__(self, num_classes=1000):
        super(InceptionV3, self).__init__()
        self.conv1 = nn.Conv2d(3, 32, kernel_size=3, stride=2, padding=1)
        self.conv2 = nn.Conv2d(32, 32, kernel_size=3, padding=1)
        self.conv3 = nn.Conv2d(32, 64, kernel_size=3, padding=1)
        self.maxpool = nn.MaxPool2d(3, stride=2, padding=1)
        self.fc = nn.Linear(64 * 5 * 5, num_classes)
        
    def forward(self, x):
        x = self.conv1(x)
        x = F.relu(x)
        x = self.conv2(x)
        x = F.relu(x)
        x = self.conv3(x)
        x = F.relu(x)
        x = self.maxpool(x)
        x = x.view(x.size(0), -1)
        x = self.fc(x)
        return x

请注意，这只是一份简化的代码，不是完整的 Inception v3 网络。