如何用pytorch写DNN网络和CNN以及MLP网络

对于如何用pytorch写DNN网络和CNN以及MLP网络，我可以给您提供一些基本的代码示例：

DNN网络：

import torch.nn as nn

class DNN(nn.Module):
    def __init__(self, input_size, hidden_size, output_size):
        super(DNN, self).__init__()
        self.fc1 = nn.Linear(input_size, hidden_size)
        self.relu = nn.ReLU()
        self.fc2 = nn.Linear(hidden_size, output_size)
        
    def forward(self, x):
        out = self.fc1(x)
        out = self.relu(out)
        out = self.fc2(out)
        return out

CNN网络：

import torch.nn as nn

class CNN(nn.Module):
    def __init__(self, input_channels, output_channels, kernel_size):
        super(CNN, self).__init__()
        self.conv = nn.Conv2d(input_channels, output_channels, kernel_size)
        self.relu = nn.ReLU()
        self.pool = nn.MaxPool2d(kernel_size=2)
        
    def forward(self, x):
        out = self.conv(x)
        out = self.relu(out)
        out = self.pool(out)
        return out

MLP网络：

import torch.nn as nn

class MLP(nn.Module):
    def __init__(self, input_size, hidden_size, output_size):
        super(MLP, self).__init__()
        self.fc1 = nn.Linear(input_size, hidden_size)
        self.relu = nn.ReLU()
        self.fc2 = nn.Linear(hidden_size, output_size)
        
    def forward(self, x):
        out = self.fc1(x)
        out = self.relu(out)
        out = self.fc2(out)
        return out

以上是基本的代码示例，您可以根据自己的需求进行修改和扩展。