yolov5 neck层

Yolov5中的neck层实现了特征融合和下采样操作。以下是Yolov5的neck层代码示例：

import torch
import torch.nn as nn

class ConvBlock(nn.Module):
    def __init__(self, in_channels, out_channels, kernel_size, stride, padding):
        super(ConvBlock, self).__init__()
        self.conv = nn.Conv2d(in_channels, out_channels, kernel_size, stride, padding)
        self.bn = nn.BatchNorm2d(out_channels)
        self.relu = nn.ReLU(inplace=True)

    def forward(self, x):
        x = self.conv(x)
        x = self.bn(x)
        x = self.relu(x)
        return x

class Neck(nn.Module):
    def __init__(self, in_channels_list, out_channels):
        super(Neck, self).__init__()
        self.conv1 = ConvBlock(in_channels_list[0], out_channels, 1, 1, 0)
        self.conv2 = ConvBlock(in_channels_list[1], out_channels, 1, 1, 0)
        self.conv3 = ConvBlock(in_channels_list[2], out_channels, 1, 1, 0)

    def forward(self, x1, x2, x3):
        feat1 = self.conv1(x1)
        feat2 = self.conv2(x2)
        feat3 = self.conv3(x3)

        return feat1, feat2, feat3

# 使用示例
in