如何实现一个简单的对抗网络GAN？

实现一个简单的生成对抗网络（Generative Adversarial Network, GAN）通常涉及以下几个步骤：

下面是一个使用PyTorch实现简单GAN的示例。这个示例将使用MNIST数据集来生成手写数字图片。

import torch
import torch.nn as nn
import torch.optim as optim
import torchvision.datasets as dsets
import torchvision.transforms as transforms
from torch.utils.data import DataLoader
import matplotlib.pyplot as plt
import numpy as np

# 定义生成器
class Generator(nn.Module):
    def __init__(self, input_size, hidden_size, output_size):
        super(Generator, self).__init__()
        self.main = nn.Sequential(
            nn.Linear(input_size, hidden_size),
            nn.ReLU(True),
            nn.Linear(hidden_size, hidden_size),
            nn.ReLU(True),
            nn.Linear(hidden_size, output_size),
            nn.Tanh()
        )

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

# 定义判别器
class Discriminator(nn.Module):
    def __init__(self, input_size, hidden_size, output_size):
        super(Discriminator, self).__init__()
        self.main = nn.Sequential(
            nn.Linear(input_size, hidden_size),
            nn.LeakyReLU(0.2, inplace=True),
            nn.Linear(hidden_size, hidden_size),
            nn.LeakyReLU(0.2, inplace=True),
            nn.Linear(hidden_size, output_size),
  ...

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