ghostconv代碼

以下是GhostConv的代码示例：

import torch
import torch.nn as nn

class GhostConv(nn.Module):
    def __init__(self, in_channels, out_channels, kernel_size, stride=1, padding=0, groups=1, bias=False):
        super(GhostConv, self).__init__()
        self.primary_conv = nn.Conv2d(in_channels, out_channels, kernel_size, stride, padding, groups=groups, bias=bias)
        self.cheap_conv = nn.Conv2d(in_channels, out_channels, 1, 1, 0, groups=groups, bias=bias)

    def forward(self, x):
        x1 = self.primary_conv(x)
        x2 = self.cheap_conv(x)
        return torch.cat([x1, x2], dim=1)

# 使用示例
input = torch.randn(1, 3, 224, 224)
conv = GhostConv(3, 64, 3)
output = conv(input)
print(output.shape)

请注意，这只是GhostConv的一个简单示例，你可以根据自己的需求进行修改和扩展。