膨胀卷积、深度可分离卷积代码

好的，关于膨胀卷积和深度可分离卷积的代码，我可以给你一些示例代码，你可以参考一下：

膨胀卷积代码示例：

import torch.nn as nn

class DilatedConv(nn.Module):
    def __init__(self, in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1):
        super(DilatedConv, self).__init__()
        self.conv = nn.Conv2d(in_channels, out_channels, kernel_size, stride=stride, padding=padding, dilation=dilation)

    def forward(self, x):
        return self.conv(x)

深度可分离卷积代码示例：

import torch.nn as nn

class DepthwiseSeparableConv(nn.Module):
    def __init__(self, in_channels, out_channels, kernel_size, stride=1, padding=0):
        super(DepthwiseSeparableConv, self).__init__()
        self.depthwise = nn.Conv2d(in_channels, in_channels, kernel_size, stride=stride, padding=padding, groups=in_channels)
        self.pointwise = nn.Conv2d(in_channels, out_channels, kernel_size=1)

    def forward(self, x):
        x = self.depthwise(x)
        x = self.pointwise(x)
        return x

这里的 `DilatedConv` 是膨胀卷积的实现，`DepthwiseSeparableConv` 是深度可分离卷积的实现。你可以根据自己的需求进行调整。