请用pytorch编写SSD目标检测模型代码，要写出全套代码

好的，以下是一个简单的SSD目标检测模型的PyTorch代码示例。请注意，这只是一个基本示例，需要根据不同的数据集和应用场景进行修改和调整。

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

class SSD(nn.Module):
    def __init__(self, num_classes):
        super(SSD, self).__init__()
        self.num_classes = num_classes

        # define layers for SSD
        self.conv1_1 = nn.Conv2d(3, 64, kernel_size=3, padding=1)
        self.conv1_2 = nn.Conv2d(64, 64, kernel_size=3, padding=1)
        self.conv2_1 = nn.Conv2d(64, 128, kernel_size=3, padding=1)
        self.conv2_2 = nn.Conv2d(128, 128, kernel_size=3, padding=1)
        self.conv3_1 = nn.Conv2d(128, 256, kernel_size=3, padding=1)
        self.conv3_2 = nn.Conv2d(256, 256, kernel_size=3, padding=1)
        self.conv3_3 = nn.Conv2d(256, 256, kernel_size=3, padding=1)
        self.conv4_1 = nn.Conv2d(256, 512, kernel_size=3, padding=1)
        self.conv4_2 = nn.Conv2d(512, 512, kernel_size=3, padding=1)
        self.conv4_3 = nn.Conv2d(512, 512, kernel_size=3, padding=1)
        self.conv5_1 = nn.Conv2d(512, 512, kernel_size=3, padding=1)
        self.conv5_2 = nn.Conv2d(512, 512, kernel_size=3, padding=1)
        self.conv5_3 = nn.Conv2d(512, 512, kernel_size=3, padding=1)

        self.fc6 = nn.Conv2d(512, 1024, kernel_size=3, padding=6, dilation=6)
        self.fc7 = nn.Conv2d(1024, 1024, kernel_size=1)

        self.conv6_1 = nn.Conv2d(1024, 256, kernel_size=1)
        self.conv6_2 = nn.Conv2d(256, 512, kernel_size=3, stride=2, padding=1)

        self.conv7_1 = nn.Conv2d(512, 128, kernel_size=1)
        self.conv7_2 = nn.Conv2d(128, 256, kernel_size=3, stride=2, padding=1)

        self.conv8_1 = nn.Conv2d(256, 128, kernel_size=1)
        self.conv8_2 = nn.Conv2d(128, 256, kernel_size=3, stride=2, padding=1)

        self.conv9_1 = nn.Conv2d(256, 128, kernel_size=1)
        self.conv9_2 = nn.Conv2d(128, 256, kernel_size=3)

        # create additional layers for detection
        self.conv4_3_norm = L2Norm(512, 20)
        self.conv7_2_norm = L2Norm(256, 10)
        self.conv8_2_norm = L2Norm(256, 10)
        self