autoencoder代码pytorch

以下是一个简单的 PyTorch 实现的自动编码器代码示例：

import torch
import torch.nn as nn

class Autoencoder(nn.Module):
    def __init__(self, input_size, hidden_size):
        super(Autoencoder, self).__init__()
        self.encoder = nn.Linear(input_size, hidden_size)
        self.decoder = nn.Linear(hidden_size, input_size)

    def forward(self, x):
        x = self.encoder(x)
        x = self.decoder(x)
        return x

input_size = 784
hidden_size = 32
model = Autoencoder(input_size, hidden_size)
criterion = nn.MSELoss()
optimizer = torch.optim.Adam(model.parameters())

# Train the model
for epoch in range(num_epochs):
    for data in dataloader:
        img, _ = data
        img = img.view(img.size(0), -1)
        img = img.to(device)
        output = model(img)
        loss = criterion(output, img)
        optimizer.zero_grad()
        loss.backward()
        optimizer.step()

这仅是一个简单的自动编码器的示例，可能需要根据实际问题进行更改。