yolov7 class conv具体代码

YOLOv7中的class conv指的是用于分类任务的卷积层。以下是YOLOv7中class conv的代码实现（使用PyTorch框架）：

import torch.nn as nn

class ClassConv(nn.Module):
    def __init__(self, in_channels, out_channels, kernel_size=1, stride=1, padding=None, groups=1, bias=True):
        super(ClassConv, self).__init__()
        if padding is None:
            self.conv = nn.Conv2d(in_channels, out_channels, kernel_size, stride, bias=bias)
        else:
            self.conv = nn.Conv2d(in_channels, out_channels, kernel_size, stride, padding, groups=groups, bias=bias)
        self.bn = nn.BatchNorm2d(out_channels)
        self.act = nn.LeakyReLU(0.1)

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

这个类接受输入通道数、输出通道数、卷积核大小、步幅、填充、分组数和是否使用偏置等参数，创建一个卷积层对象。在forward函数中，先进行卷积、BN和激活操作，然后返回结果。